Abstract: An approach for the measurement of surface displacement fields in three dimensions is presented based on the combination of two-dimensional digital image correlation with fringe projection. Only a single RGB image is required at each deformation state, thereby allowing real-time data acquisition, which is achieved using red speckle and projected blue fringes that are captured in the single image and separated using a Bayer filter. The approach allows both a perpendicular alignment relative to a flat reference surface and self-calibration, i.e., no calibration object is employed. The minimum measurement uncertainty of such a system is found to be 0.0083±0.00239 and 0.0238±0.0068 mm, respectively, for the in-plane and out-of-plane displacements. The potential of the approach is demonstrated for an elastic membrane undergoing large (5 to 20 mm) applied out-of-plane displacements, and the results show no significant difference (<1%) in the measured in-plane displacement fields compared with a commercially available system for stereoscopic digital image correlation.

Abstract: Information is encoded in an image signal by exploiting spectral differences between colors that appear the same when rendered. These spectral differences are detected using image sensing that discerns the spectral differences. Spectral difference detection methods include using sensor-synchronized spectrally-structured-light imaging, 3D sensors, imaging spectrophotometers, and higher resolution Bayer pattern capture relative to resolution of patches used to convey a spectral difference signal.

Abstract: The high density of pixels in modern color sensors provides an opportunity to experiment with new color filter array (CFA) designs. A significant bottleneck in evaluating new designs is the need to create demosaicking, denoising and color transform algorithms tuned for the CFA. To address this issue, we developed a method(local, linear, learned or L3) for automatically creating an image processing pipeline. In this paper we describe the L3 algorithm and illustrate how we created a pipeline for a CFA organized as a 2×2 RGB/Wblock containing a clear (W) pixel. Under low light conditions, the L3 pipeline developed for the RGB/W CFA produces images that are superior to those from a matched Bayer RGB sensor. We also use L3 to learn pipelines for other RGB/W CFAs with different spatial layouts. The L3 algorithm shortens the development time for producing a high quality image pipeline for novel CFA designs.

Abstract: The expensive photosensors of scientific cameras are commonly used in the wide variety of research fields. However, photosensors that are implemented in DSLR cameras are seen to be an appropriate substitution in order to decrease price/quality ratio or even receive additional features. In this article different scientific applications of DSLR cameras' photosensors with Bayer filter as well as calibration methods of its spectral characteristics are discussed. The approach, based on determination of latter and usage of its features, is shown to increase SNR of the color reconstructed images in digital holography.

Abstract: We present an alternative method of color imaging. It utilizes a single standard Si-based image sensor and a clear aperture, tunable, color filter. Within this scheme, three monochromatic frames are taken; each is acquired with a single color and with a fraction of the total acquisition duration. This scheme offers several advantages compared to standard Bayer-demosaicing schemes. Among them – significantly higher resolution, flexibility in exposure durations, improved noise performance and in sum – better image quality. This paper presents both color filter design and the adjusted image pipeline. Lastly, the proposed imaging scheme and the Bayer scheme are compared in terms of MSE.

Abstract: The invention provides an image processing method which includes the following steps: obtaining a source image of a Bayer pattern color array; executing a first-order image processing on the source image to generate a first luminance and chrominance format image; executing a second-order image processing on the source image so as to generate a second luminance and chrominance format image; then generating a noise inhibition image after executing noise filtering processing on the first brightness and chrominance format image; and firstly carrying out weighting processing on a luminance image in the noise inhibition image and a luminance image in the second luminance and chrominance format image and then combining a chrominance image in the second luminance and chrominance format image so as to generate a processed image. The noise reduction degree of the noise inhibition image is higher than the noise reduction degree of the second luminance and chrominance format image.

Abstract: Most digital cameras use a single sensor coupled with a Color Filter Array (CFA) to capture images, and apply demosaicking to interpolate the full color images. In reality, the CFA image is noisy, which causes problems in the demosaicking process. This paper proposes a Joint Denoising and Demo-saicking based on inter-Color correlation (JDDC) scheme. We propose a new framework that linearly combines an extracted luminance image and a low-passed RGB images to get a full color image. Given the noise in the extracted luminance image and the low-passed RGB images are non-stationary and partially correlated, we modify the classical Non-Local Means (NLM) filter to denoise the extracted luminance image and the low-passed RGB images before the combination. Experimental results verify the effectiveness of the proposed scheme both objectively and subjectively.

Abstract: Systems and methods for generating high dynamic images from interleaved Bayer array data with high spatial resolution and reduced sampling artifacts. Bayer array data are demosaiced into components of the YUV color space before deinterleaving. The Y component and the UV components can be derived from the Bayer array data through demosiac convolution processes. A respective convolution is performed between a convolution kernel and a set of adjacent pixels of the Bayer array that are in the same color channel. A convolution kernel is selected based the mosaic pattern of the Bayer array and the color channels of the set of adjacent pixels. The Y data and UV data are deinterleaved and interpolated into frames of short exposure and long exposures in the second color space. The short exposure and long exposure frames are then blended and converted back to a RGB frame representing a high dynamic range image.

Abstract: Modern video cameras normally only capture a single color per pixel, commonly arranged in a Bayer pattern. This means that we must restore the missing color channels in the image or the video frame in post-processing, a process referred to as debayering. In a live video scenario, this operation must be performed efficiently in order to output each frame in real-time, while also yielding acceptable visual quality. Here, we evaluate debayering algorithms implemented on a GPU for real-time panoramic video recordings using multiple 2K-resolution cameras.

Abstract: Since the adoption of digital video cameras and cross-correlation methods for particle image velocimetry (PIV), the use of color images has largely been abandoned. Recently, however, with the re-emergence of color-based stereo and volumetric techniques, and the extensive use of color microscopy, color imaging for PIV has again become relevant. In this work, we explore the potential advantages of color PIV processing by developing and proposing new methods for handling multi-color images. The first method uses cross-correlation of every color channel independently to build a color vector cross-correlation plane. The vector cross-correlation can then be searched for one or more peaks corresponding to either the average displacement of several flow components using a color ensemble operation, or for the individual motion of colored particles, each with a different behavior. In the latter case, linear unmixing is used on the correlation plane to separate each known particle type as captured by the different color channels. The second method introduces the use of quaternions to encode the color data, and the cross-correlation is carried out simultaneously on all colors. The resulting correlation plane can be searched either for a single peak, corresponding to the mean flow or for multiple peaks, with velocity phase separation to determine which velocity corresponds to which particle type. Each of these methods was tested using synthetic images simulating the color recording of noisy particle fields both with and without the use of a Bayer filter and demosaicing operation. It was determined that for single-phase flow, both color methods decreased random errors by approximately a factor of two due to the noise signal being uncorrelated between color channels, while maintaining similar bias errors as compared to traditional monochrome PIV processing. In multi-component flows, the color vector correlation technique was able to successfully resolve displacements of two distinct yet coupled flow components with errors similar to traditional grayscale PIV processing of a single phase. It should be noted that traditional PIV processing is bound to fail entirely under such processing conditions. In contrast, the quaternion methods frequently failed to properly identify the correct velocity and phase and showed significant cross talk in the measurements between particle types. Finally, the color vector method was applied to experimental color images of a microchannel designed for contactless dielectrophoresis particle separation, and good results were obtained for both instantaneous and ensemble PIV processing. However, in both the synthetic color images that were generated using a Bayer filter and the experimental data, a significant peak-locking effect with a period of two pixels was observed. This effect is attributed to the inherent architecture of the Bayer filter. In order to mitigate this detrimental artifact, it is suggested that improved image interpolation or demosaicing algorithms tuned for use in PIV be developed and applied on the color images before processing, or that cameras that do not use a Bayer filter and therefore do not require a demosaicing algorithm be used for color PIV.

Abstract: The present disclosure relates to a method for manufacturing a color filter being capable of suppressing residue from being generated on a colored layer planarized by a planarization treatment, a color filter, and a solid-state imaging device.

Abstract: Recently, color filter array patterns based on optimal design by reducing interchannel aliasing have been developed. Although these optimally subsampled patterns produce less degradation of resolution for the images in daylight about 6500 K, aliasing and grid effect become more prominent under the different lighting conditions. Moreover, the color interpolation (CI) for Bayer pattern cannot be utilized for these patterns. Since it is impossible to change coated patterns according to various conditions, CI algorithms have to compensate for light variations. In this letter, a method for generating intermediate quincuncial pattern is proposed for two patterns. Also, edge adaptive interpolation for the quincuncial pattern is carried out. Experimental results show that the proposed method reduces aliasing and grid effect.

Abstract: —In this paper a region-adaptive demosaicking algorithm with low computational complexity for single-sensor digital cameras is proposed. The proposed algorithm firstly divides the input image into two kinds of regions and then adopts different interpolation methods for each type. The proposed interpolation method makes full use of bilinear’s fast execution speeds in the smooth region. And it directly extracts and recovers edge information with weighted values of multidirectional components in edge regions. Experimental results show that the proposed method has an outstanding performance not only in subjective visual quality but also in terms of composite peak signal to noise ratio (CPSNR).

Abstract: Provided is an image capturing module including a microlens array that collects light from a subject, which is imaged at an image plane; a filter that allows light in specific wavelength bands in the collected light to pass therethrough; and an image capturing device that acquires images of the light passing through the filter, wherein the filter is formed by arraying a plurality of RGB filter portions and a plurality of narrow-band filter portions, the image capturing device includes a plurality of color-wavelength obtaining regions and a plurality of narrow-band-wavelength obtaining regions, and the microlens array includes a plurality of first microlenses corresponding to the respective color-wavelength obtaining regions and a plurality of second microlenses corresponding to the respective narrow-band-wavelength obtaining regions, and the first microlenses are each disposed so that the light from the subject imaged at the image plane reaches at least one of the color-wavelength obtaining regions.

Abstract: It is not easy to acquire a desired high dynamic range (HDR) image directly from a camera due to the limited dynamic range of most image sensors. Therefore, generally, a post-process called HDR image reconstruction is used, which reconstructs an HDR image from a set of differently exposed images to overcome the limited dynamic range. However, conventional HDR image reconstruction methods suffer from noise factors and ghost artifacts. This is due to the fact that the input images taken with a short exposure time contain much noise in the dark regions, which contributes to increased noise in the corresponding dark regions of the reconstructed HDR image. Furthermore, since input images are acquired at different times, the images contain different motion information, which results in ghost artifacts. In this paper, we propose an HDR image reconstruction method which reduces the impact of the noise factors and prevents ghost artifacts. To reduce the influence of the noise factors, the weighting function, which determines the contribution of a certain input image to the reconstructed HDR image, is designed to adapt to the exposure time and local motions. Furthermore, the weighting function is designed to exclude ghosting regions by considering the differences of the luminance and the chrominance values between several input images. Unlike conventional methods, which generally work on a color image processed by the image processing module (IPM), the proposed method works directly on the Bayer raw image. This allows for a linear camera response function and also improves the efficiency in hardware implementation. Experimental results show that the proposed method can reconstruct high-quality Bayer patterned HDR images while being robust against ghost artifacts and noise factors.

Abstract: A camera array system includes an image sensor device, a hybrid color filter array disposed above the image sensor device, and a lens array disposed above the hybrid color filter array. The hybrid color filter array includes plural kinds of monochromatic color filters and at least one mosaic filter; and the lens array includes a number of optic lenses. The at least one mosaic filter is utilized to perform stereo matching in order to estimate depth information.

Abstract: Since capturing three color channels (red, green, and blue) per pixel increases the cost of digital cameras, most digital cameras capture only one color channel per pixel using a single image sensor. The images pass through a color filter array before being captured by the image sensor. Demosaicing is the process of reconstructing the missing color channels of the pixels in the color filtered image using their available neighboring pixels. Alternating Projections (AP) is one of the highest quality image demosaicing algorithms, and it has very high computational complexity. Therefore, in this paper, a high performance AP image demosaicing hardware is proposed. This is the first AP image demosaicing hardware in the literature. The proposed hardware is implemented using Verilog HDL. The Verilog RTL code is verified to work correctly in a Xilinx Virtex 6 FPGA. The FPGA implementation can process 31 full HD (1920×1080) images per second.

Abstract: A method is provided for extracting RGB and NW using an RGBW sensor that improves image information processing performance by simultaneously extracting RGB and NIR image information using the RGBW sensor in which pixels of an RGB filter and pixels of a clear filter are coupled, and reducing cost by extracting the NIR image information while not using an infrared cutoff filter is provided. The method includes transmitting, by light, an RGBW filter, and extracting an RGBW image value (R_c, G_c, B_c, W_c) captured by sensing the transmitted light by the RGBW sensor and extracting an RGB value. In addition, the method includes an NIR value by multiplying the captured RGBW image value with an inverse matrix (A) value.

Abstract: Embodiments include a method comprising: receiving a source image comprising a plurality of pixels, wherein individual pixels of the plurality of pixels of the source image comprise a corresponding pixel value that is associated with a corresponding color of a plurality of colors, and wherein a first pixel of the plurality of pixels of the source image comprises a first pixel value that is associated with a first color of the plurality of colors; and for the first pixel of the plurality of pixels of the source image, estimating (i) a second pixel value that is associated with a second color of the plurality of colors and (iii) a third pixel value that is associated with a third color of the plurality of colors.

Abstract: Demosaicing is an algorithm used to reconstruct a color image from the incomplete color samples of a color filter array (CFA). Most demosaicing algorithms can be broadly classified into spatial-domain and frequency-domain approaches. Despite significant progress in the past decade, current state of the art demosaicing algorithms still tend to produce artifacts at high-saturation edges. In this paper we propose a new approach to demosaicing — example based. Comparative experimental evaluation shows that example-based demosaicing (EBD) produces visually superior, artifact-free results.

Abstract: The main idea behind wavelet based demosaicing with spatial refinement is to reconstruct the full reso lution color image from the mosaiced image. In this study, a new effective wavelet based demosaicing algorith m for interpolating the missing color components in Bayer ’s Color Filter Array (CFA) pattern is proposed. Th is interpolation technique uses the interchannel corre lation among the high frequency subbands to determine the missing pixels in each color channel, followed by a refining step in spatial domain which uses non-ite rative technique that enforces color difference rule with fewer computations. As a result, the proposed demosaicing method yields better performance than bilinear, edg e based and subband based demosaicing methods.

Abstract: Among semi-quantitative or fully quantitative lateral flow assay readers, an image sensor-based instrument has been widely used because of its simple setup, cheap sensor price, and compact equipment size. For all previous approaches, monochrome CCD or CMOS cameras were used for lateral flow assay imaging in which the overall intensities of all colors were taken into consideration to estimate the analyte content, although the analyte related color information is only limited to a narrow wavelength range. In the present work, we introduced a color CCD camera as a sensor and a color decomposition method to improve the sensitivity of the quantitative biosensor system which utilizes the lateral flow assay successfully. The proposed setup and image processing method were applied to achieve the quantification of imitatively dispensed particles on the surface of a porous membrane first, and the measurement result was then compared with that using a monochrome CCD. The compensation method was proposed in different illumination conditions. Eventually, the color decomposition method was introduced to the commercially available lateral flow immunochromatographic assay for the diagnosis of myocardial infarction. The measurement sensitivity utilizing the color image sensor is significantly improved since the slopes of the linear curve fit are enhanced from 0.0026 to 0.0040 and from 0.0802 to 0.1141 for myoglobin and creatine kinase (CK)-MB detection, respectively.

Abstract: Capsule endoscopy is a method for recording images of the digestive tract. A patient swallows a capsule containing a tiny camera, which captures images that are then transmitted wirelessly to an external receiver for examination by a physician. The images are captured using a Bayer filter mosaic, such that each pixel in the raw captured images represents only one color: red, green or blue. Due to limited computational capabilities in the capsule and bandwidth constraints, low-complexity and efficient compression of Bayer endoscopy images is required before transmission. In this paper, we focus on the JPEG algorithm, and show how to adapt it for compressing Bayer endoscopy images. We show that by transformation to the YCgCo color space and appropriate optimization of parameters, significant improvement is achieved over the standard JPEG.

Abstract: Recently, most digital capture devices have the single image sensor such as CCD and CMOS sensor with a color filter array (CFA), which is Bayer pattern. To reconstruct a full color image, missing elements for each channel are estimated from neighboring pixels in inter, intra, or both channels. This processing is called interpolation or demosaicing (Demosaicking). In this paper, we presents the improved demosaicking method based on the multi-scale edge-directed filter. Specially, this method correct the demosaicking error in the refinement step. We demonstrated the good demosaicking performance in experimental results.

Abstract: This paper proposes a new possible noise model and its application to Bayer color filter array (CFA). We studied effects of several noise models on three Bayer patterns. For instance, current Bayer CFA uses RGGB pattern which contains two green pixels, a red and a blue pixels in a pair. However, one may consider other color combinations such as RRGB or RGBB patterns. To investigate RGGB pattern's superiority, we research each pattern in different noise model and its level. We also studied how to generate noisy image from noisy-free image. In addition, conventional noise models do not consider white balance, gamma and tone correction issues. In this paper, we suggest adding such components in the model. Experimental results show that the new noise model is reasonable than the conventional ones.

Abstract: Image demosaicing is a problem of interpolating full-resolution color images from so-called color-filter-array (CFA) samples. Among the various CFA patterns, Bayer pattern has been the most familiar choice and demosaicing of Bayer pattern has attracted renewed interest in the recent years. In this paper we propose a new modified color filter array interpolation method which uses the spatial filters to eliminate the false color artifacts and a modified bilinear interpolator. The proposed method has the advantage of low power which could be observed from the synthesis report.

Abstract: Provided are a color filter capable of improving an aperture ratio of a BM, a liquid crystal display apparatus, and a method of manufacturing the color filter For an R layer disposed in an opening, a right exposure part and a left exposure part of a G layer disposed in an opening adjacent to a right side of the opening are patterned by exposing using an alignment mark Briefly, portions of the RGB layers facing each other in a horizontal direction, which are respectively to be disposed in two openings adjacent to each other in the horizontal direction, may be patterned by exposing using the same alignment mark As a result, unnecessarily close arrangement or separated arrangement of the RGB layers caused by referring to the different alignment marks does not occur Consequently, there is no need to increase a BM between the RGB layers in the horizontal direction Therefore, an aperture ratio of the BM is improved

Abstract: In this paper, we introduce a novel framework for lossless/near-lossless (LS/NLS) color image coding assisted by an inverse demosaicing. Conventional frameworks are typically based on prediction (and quantization for NLS coding) followed by entropy coding, such as the JPEG-LS for bit rate saving. The approach of this work is totally different from the conventional ones. Basically, color images are created by demosaicing Bayer-pattern color filter array (CFA) whose operator can be expressed as square matrices. By using the (pseudo) inverse matrix of a joint demosaicing and color-to-gray conversion, the proposed decoder can recover the color image from its corresponding gray image data which is losslessly transmitted by the proposed encoder. Thus, LS/NLS color image reconstruction can be achieved while saving a bit rate significantly. In addition, using the same framework of color image coding, LS/NLS CFA coding can be realized by a comparable bit rate with JPEG-LS.