https://researchportal.port.ac.uk/portal/files/7059144/1_s2.0_S0925231217305246_main.pdf

Underwater image enhancement via extended multi-scale Retinex

Poor weather conditions, such as fog, haze, and mist, cause visibility degradation in captured images. Existing imaging devices lack the ability to effectively and efficiently mitigate the visibility degradation caused by poor weather conditions in real time. Image depth information is used to eliminate hazy effects by using existing physical model-based approaches. However, the imprecise depth information always affects dehazing performance. This article proposes an image fusion-based algorithm to enhance the performance and robustness of image dehazing. Based on a set of gamma-corrected underexposed images, pixelwise weight maps are constructed by analyzing both global and local exposedness to guide the fusion process. The spatial-dependence of luminance of the fused image is reduced, and its color saturation is balanced in the dehazing process. The performance of the proposed solution is confirmed in both theoretical analysis and comparative experiments.

A Novel Fast Single Image Dehazing Algorithm Based on Artificial Multiexposure Image Fusion

We propose a novel image-dehazing technique based on the minimization of two energy functionals and a fusion scheme to combine the output of both optimizations. The proposed fusion-based variational image-dehazing (FVID) method is a spatially varying image enhancement process that first minimizes a previously proposed variational formulation that maximizes contrast and saturation on the hazy input. The iterates produced by this minimization are kept, and a second energy that shrinks faster intensity values of well-contrasted regions is minimized, allowing to generate a set of difference-of-saturation (DiffSat) maps by observing the shrinking rate. The iterates produced in the first minimization are then fused with these DiffSat maps to produce a haze-free version of the degraded input. The FVID method does not rely on a physical model from which to estimate a depth map, nor it needs a training stage on a database of human-labeled examples. Experimental results on a wide set of hazy images demonstrate that FVID better preserves the image structure on nearby regions that are less affected by fog, and it is successfully compared with other current methods in the task of removing haze degradation from faraway regions.

Fusion-Based Variational Image Dehazing

To improve contrast and restore color for underwater images without suffering from insufficient details and color cast, this paper proposes a fusion algorithm for different color spaces based on co...

Contrast Limited Adaptive Histogram Equalization-Based Fusion in YIQ and HSI Color Spaces for Underwater Image Enhancement

Optical remote sensing image enhancement with weak structure preservation via spatially adaptive gamma correction

Biologically inspired image enhancement based on Retinex

The invention pertains to the technical field of image processing and pattern recognition, and the invention discloses a pedestrian fast detection method based on videos Human positive samples are collected in an actual scene in two modes including the automatic mode and the manual mode to train a human star detection template in a particular scene; video monitoring images are acquired and image pretreatment is performed so as to perform appropriate compensation on illumination mainly; treatment is performed on time domain information of an image moving object to extract the foreground region of the moving object; the pyramid layering range is determined according to the size of the foreground region to judge the foreground region whether needs to be fused, and the pyramid layers are redivided; matching is performed between the trained pedestrian template and the processed image to determine the pedestrian position; and fusion optimization is performed on the pedestrian position to select the optimal pedestrian position and mark the pedestrian The method of the invention is suitable for the field of tracking of a plurality of human objects in different scenes to satisfy the detection robustness and real-time performance requirements at the same time

Pedestrian fast detection method based on videos

The invention discloses a bilateral filter-based single image defogging method. The bilateral filter-based single image defogging method is used for reasonably restoring degraded images influenced by hazy weather. The bilateral filter-based single image defogging method comprises the following steps: gaining a dark channel picture of an original atomization image so as to obtain atmosphere light intensity; estimating an atmosphere dissipative function by utilizing two times of bilateral filtering; obtaining a medium propagation function by using the arithmetic expression of the atmosphere dissipative function; weakening a local bright area; obtaining a clear image by using an atmospheric scattering model. The bilateral filter-based single image defogging method can be used for restoring the scenery information of the atomization image clearly and naturally and improving the visual effect of the image; the method is simple in complexity and high in running speed, thus good application value is supplied for a real-time monitoring system.

Yin Chuanli

Papers

Biologically inspired image enhancement based on Retinex

Pedestrian fast detection method based on videos

Bilateral filter-based single image defogging method