Since the light is absorbed and scattered while traveling in water, color distortion, under-exposure and fuzz are three major problems of underwater imaging. In this paper, a novel retinex-based enhancing approach is proposed to enhance single underwater image. The proposed approach has mainly three steps to solve the problems mentioned above. First, a simple but effective color correction strategy is adopted to address the color distortion. Second, a variational framework for retinex is proposed to decompose the reflectance and the illumination, which represent the detail and brightness respectively, from single underwater image. An effective alternating direction optimization strategy is adopted to solve the proposed model. Third, the reflectance and the illumination are enhanced by different strategies to address the under-exposure and fuzz problem. The final enhanced image is obtained by combining use the enhanced reflectance and illumination. The enhanced result is improved by color correction, lightens dark regions, naturalness preservation, and well enhanced edges and details. Moreover, the proposed approach is a general method that can enhance other kinds of degraded image, such as sandstorm image.

A retinex-based enhancing approach for single underwater image

Underwater images often suffer from color shift and contrast degradation due to the absorption and scattering of light while traveling in water. In order to handle these issues, we present and solve two sub-problems to improve underwater image quality. First, we introduce an effective color correcting strategy based on piece-wise linear transformation to address the color distortion. Then we discuss a novel optimal contrast improvement method, which is efficient and can reduce artifacts, to address the low contrast. Since most operations are pixel-wise calculations, the proposed method is straightforward to implement and appropriate for real-time application. In addition, prior knowledge about imaging conditions is not required. Experiments show an improvement in the enhanced image of color, contrast, naturalness and object prominence.

Two-step approach for single underwater image enhancement

Deriving inherent optical properties from background color and underwater image enhancement

A retinex-based enhancing approach for single underwater image(图像处理旗舰会议)

Underwater dam crack detection and classification based on visible images is a challenging task. The underwater environment is very complex with uneven illumination and serious noise problems, which often leads to the distortion of detection. In addition, there are few methods suitable for underwater dam crack classification. To solve these problems, a novel underwater dam crack detection and classification approach is proposed. Firstly, a dodging algorithm is used to eliminate the uneven illumination in the underwater visible images. Subsequently, a crack detection approach is proposed, where the local characteristics of image blocks and the global characteristics of connected domains are both used based on the analysis of the statistical properties of dam crack images. Finally, an improved evidence theory-based crack classification algorithm is proposed after the crack detection. Experimental results show that the proposed approach is able to detect underwater dam cracks and classify them accurately and...

A detection and classification approach for underwater dam cracks

The inspection of offshore parks, dam walls and other infrastructure under water is expensive and time consuming, because such constructions must be inspected manually by divers. Underwater buildings have to be examined visually to find small cracks, spallings or other deficiencies. Automation of underwater inspection depends on established water-proved imaging systems. Most underwater imaging systems are based on acoustic sensors (sonar). The disadvantage of such an acoustic system is the loss of the complete visual impression. All information embedded in texture and surface reflectance gets lost. Therefore acoustic sensors are mostly insufficient for these kind of visual inspection tasks. Imaging systems based on optical sensors feature an enormous potential for underwater applications. The bandwidth from visual imaging systems reach from inspection of underwater buildings via marine biological applications through to exploration of the seafloor. The reason for the lack of established optical systems for underwater inspection tasks lies in technical difficulties of underwater image acquisition and processing. Lightening, highly degraded images make a computational postprocessing absolutely essential.

Model based image restoration for underwater images

In this contribution we present a method for handling merged detections in video-based Multi-Target-Tracking applications. Merged detections occur when two or more objects evoke one joint detection, i.e. when measurements stemming from multiple objects cannot be resolved by the sensor. In video-based applications this is the case when the segmentation fails to separate blobs belonging to different objects. The proposed approach is based on the specification of candidate merge events and resulting data association events. We propose a concept which allows recognition of the merge events and a correct track update in case of identified merges. This is done by generating artificial (virtual) measurements (measurement reconstruction) through decomposition of respective detections. The globally optimal solution is achieved by weighting different candidate hypotheses according to their a-posteriori probabilities.

Probabilistic Handling of Merged Detections in Multi Target Tracking

Die Erfindung betrifft eine Vorrichtung (1) mit einer ersten Bilderfassungseinrichtung (11) mit einem ersten Erfassungsbereich (21) und einer zweiten Bilderfassungseinrichtung (12) mit einem zweiten Erfassungsbereich (22), wobei der erste Erfassungsbereich (21) und der zweite Erfassungsbereich (22) zumindest teilweise uberlappen, und die Vorrichtung weiterhin zumindest eine Lichtquelle (31, 32, 33) aufweist, welche dazu eingerichtet ist, Licht aus unterschiedlichen Einfallsrichtungen in zumindest einen Erfassungsbereich (21, 22) zu emittieren. Weiterhin betrifft die Erfindung ein Verfahren zur Bestimmung der Topografie einer Oberflache (50) eines Pruflings (5).

Verfahren und Vorrichtung zur Bestimmung der Topografie einer Oberflache

Abstract This paper presents an overview of the challenges encountered in underwater sensing. Two state-of-the-art approaches are presented dealing with optic and acoustic sensor data processing. Employing suitable methods for the different modalities enables fusion of the information contained in the optic radiative transfer and acoustic reflectivity.

Approaches to Acoustic and Visual Underwater Sensing

When technical goods, like mainboards and other electronic components, are produced, quality assurance (QA) is very important. To achieve this goal, different optical microscopes can be used to analyze a variety of specimen to gain comprehensive information by combining the acquired sensor data. In many industrial processes, cameras are used to examine these technical goods. Those cameras can analyze complete boards at once and offer a high level of accuracy when used for completeness checks. When small defects, e.g. soldered points, need to be examined in detail, those wide area cameras are limited. Microscopes with large magnification need to be used to analyze those critical areas. But microscopes alone cannot fulfill this task within a limited time schedule, because microscopic analysis of complete motherboards of a certain size is time demanding. Microscopes are limited concerning their depth of field and depth of focus, which is why additional components like XY moving tables need to be used to examine the complete surface. Yet today’s industrial production quality standards require a 100 % control of the soldered components within a given time schedule. This level of quality, while keeping inspection time low, can only be achieved when combining multiple inspection devices in an optimized manner. This paper presents results and methods of combining industrial cameras with microscopy instrumenting a classificatory based approach intending to keep already deployed QA processes in place but extending them with the purpose of increasing the quality level of the produced technical goods while maintaining high throughput.

Integrating Microscopic Analysis into Existing Quality Assurance Processes

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