Topic
Flat-field correction
About: Flat-field correction is a research topic. Over the lifetime, 77 publications have been published within this topic receiving 817 citations.
Papers published on a yearly basis
Papers
24 Jul 1998
TL;DR: The variable exposure flat-field correction methodology proposed here provides an improved match to the fixed-point noise superimposed in the uncorrected image, particularly for the higher spatial frequencies in the image as demonstrated by DQE(f) measurements.
Abstract: The effects of the stationary noise patterns and variable pixel responses that commonly occur with uniform exposure of digital detectors can be effectively reduced by simple 'flat- field' image processing methods. These methods are based upon a linear system response and the acquisition of an image (or images) acquired at a high exposure to create an inverse matrix of values that when applied to an uncorrected image, remove the effects of the stationary noise components. System performance is optimized when the correction image is totally free of statistical variations. However, the stationary noise patterns will not be effectively removed for flat-field images that are acquired at a relatively low exposure or for systems with non-linear response to incident exposure variations. A reduction in image quality occurs with the incomplete removal of the stationary noise patterns, resulting in a loss of detective quantum efficiency of the system. A more flexible approach to the global flat-field correction methodology is investigated using a pixel by pixel least squares fit to 'synthesize' a variable flat-field image based upon the pixel value (incident exposure) of the image to be corrected. All of the information is stored in two 'equivalent images' containing the slope and intercept parameters. The methodology provides an improvement in the detective quantum efficiency (DQE) due to the greater immunity of the stationary noise variation encoded in the slope/intercept parameters calculated on a pixel by pixel basis over a range of incident exposures. When the raw image contains a wide range of incident exposures (e.g., transmission through an object) the variable exposure flat-field correction methodology proposed here provides an improved match to the fixed-point noise superimposed in the uncorrected image, particularly for the higher spatial frequencies in the image as demonstrated by DQE(f) measurements. Successful application to clinical digital mammography biopsy images has been demonstrated, and benefit to other digital detectors appears likely.
214 citations
TL;DR: Experiments show that the proposed dynamic flat field Correction leads to a substantial reduction of systematic errors in projection intensity normalization compared to conventional flat field correction.
Abstract: In X-ray imaging, it is common practice to normalize the acquired projection data with averaged flat fields taken prior to the scan. Unfortunately, due to source instabilities, vibrating beamline components such as the monochromator, time varying detector properties, or other confounding factors, flat fields are often far from stationary, resulting in significant systematic errors in intensity normalization. In this work, a simple and efficient method is proposed to account for dynamically varying flat fields. Through principal component analysis of a set of flat fields, eigen flat fields are computed. A linear combination of the most important eigen flat fields is then used to individually normalize each X-ray projection. Experiments show that the proposed dynamic flat field correction leads to a substantial reduction of systematic errors in projection intensity normalization compared to conventional flat field correction.
104 citations
TL;DR: The results indicate that the variable flat-field correction method with the appropriate polynomial fit provides excellent correction throughout the entire exposure range.
Abstract: In this Technical Note, the effects of different flat-field techniques are examined for a cesium iodide flat panel detector, which exhibited a slightly nonlinear exposure response. The results indicate that the variable flat-field correction method with the appropriate polynomial fit provides excellent correction throughout the entire exposure range. The averaged normalized variation factor, used to assess the nonuniformity of the flat-field correction, decreased from 30.76 for the fixed correction method to 4.13 for the variable flat-field correction method with a fourth-order polynomial fit for the 60 kVp spectrum, and from 16.42 to 3.97 for the 95 kVp spectrum.
66 citations
CERN1
01 Sep 2003-Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment
TL;DR: The field of pixel detectors has grown strongly in recent years through progress in CMOS technology, which permits many hundreds of transistors to be implemented in an area of 50-200μm2 as mentioned in this paper.
Abstract: The field of pixel detectors has grown strongly in recent years through progress in CMOS technology, which permits many hundreds of transistors to be implemented in an area of 50–200 μm2. Pulse processing electronics with noise of the order of 100 e− RMS permits to distinguish photons of a few kilo-electron-Volts from background noise. Techniques are under development, which should allow single chip systems (area ∼1 cm2) to be extended to larger areas. This paper gives an introduction into the concept of quantum imaging using direct conversion in segmented semiconductor arrays. An overview of projects from this domain using strip, pad and in particular hybrid pixel detectors will be presented. One of these projects, the Medipix project, is described in more detail. The effect of different correction methods like threshold adjustment and flat field correction is illustrated and new measurement results and images are presented.
62 citations
TL;DR: The extensive experiments carried out using cell cultures, histological samples and synthetic images prove that the effective multi‐image based method proposed almost always yields the best results and in worst cases are comparable to those achieved by using homogeneous reference objects.
Abstract: Vignetting is the radial attenuation effect of the image's brightness intensity from the center of the optical axis to the edges. To perform quantitative image analyses it is mandatory to take into account this effect, intrinsic of the acquisition system. Many image processing steps, such as segmentation and object tracking, are strongly affected by vignetting and the effect becomes particularly evident in mosaicing. The most common approach to compensate the attenuation of the image's brightness intensity is to estimate the vignetting function from a homogeneous reference object, typically an empty field, and to use it to normalize the images acquired under the same microscope set-up conditions. However, several reasons lead to the use of image-based methods to estimate the vignetting function from the images themselves. In this work, we propose an effective multi-image based method suitable for real-time applications. It is designed to correct vignetting in wide field light microscopy images. The vignetting function is computed stemming from a background built incrementally from the proposed background segmentation algorithm, validated on several manually segmented images. The extensive experiments carried out using cell cultures, histological samples and synthetic images prove that our method almost always yields the best results and in worst cases are comparable to those achieved by using homogeneous reference objects.
59 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2021 | 3 |
| 2020 | 3 |
| 2019 | 5 |
| 2018 | 5 |
| 2017 | 7 |
| 2016 | 6 |