FPGA Implementation of Low-Light Enhancement Algorithm_ To Enhance Low-Light Images/Videos Matlab

This example performs LLE by inverting an input image and then applying a de-haze algorithm on the inverted image.

After inverting the low-light image, the pixels representing non-sky region have low intensities in at least one color channel.

The algorithm consists of six stages. Step 1: Scaling & Inversion The input image   is converted to range [0,1] by dividing by 255 and then inverting pixel-wise. Step 2: Dark Channel Estimation The dark channel is estimated by finding the pixel-wise minimum across all three channels of the inverted image. Step 3: Refinement The airlight image from the previous stage is refined by iterative smoothing. This stage consists of five filter iterations with a 3-by-3 kernel for each stage. Step 4: Non-Linear Correction To reduce over-enhancement, the refined image is corrected using a non-linear correction. Step 5: Restoration Restoration is performed pixel-wise across the three channels of the inverted and corrected image. Step 6: Inversion To obtain the final enhanced image, this stage inverts the output of the restoration stage, and scales to the range [0,255].

The figure shows the input image and the enhanced output images obtained from the LLESimplified subsystem and the LLEHDL subsystem. Click here to get the simulink file: https://drive.google.com/file/d/1nBBRRzjqXsKmImOCqdXWTZ8NXM6hmi3m/view?usp=sharing