In view of the low contrast and large colour deviation of the image captured by the camera in foggy weather, it is proposed to modify the parameters of atmospheric light and transmittance through dual channels, refine the transmittance by the tolerance mechanism, and obtain the dehazed image in reverse according to the atmospheric scattering model function. Combined with the parallel operation and high-speed characteristics of FPGA (Field Programmable Gate Array) hardware platform, the proposed algorithm is parallelized and simplified, and the implementation of dark channel dehazing hardware based on FPGA is designed. After testing by MATLAB and ModelSim, the restored image is clear and distortion-free.
Due to the absorption and scattering of light by water medium and suspended particles, underwater images come with color deviation and blurred details. For different light absorption in different underwater environments, an adaptive compensation method for local color channels is proposed to enhance the compensation for severe attenuation areas, which is suitable for underwater scenes with multiple color deviations. The dark channel prior is used to remove the detail blurring caused by scattering, the multi-scale Gaussian convolution and gamma correction are adopted to estimate the local light, and the tolerance parameter is used to increase the transmittance of bright areas to compensate for the dark channel prior conditions. The enhanced image quality is evaluated by Underwater Image Quality Measurement (UIQM), Average Gradient (AG), and entropy. Experimental data show that the method improves the color deviation of underwater images in different environments, enhances color information, and improves the contrast of images.
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