Digital Image Process - Final Homework You are given a paper and the corresponding source code. In this paper, the author proposed an algorithm to remove the haze in an image. Figure 1. Haze removal using a single image. (a) input haze image. (b) image after haze removal by our approach. (c) our recovered depth map Paper: Single Image Haze Removal Using Dark Channel Prior Code: https://github.com/He-Zhang/image_dehaze This is the code implemented in Python, you can find other language versions in the github easily. Your tasks: 1. Try to understand the paper and code, then choose some images with haze as input, run the code to get images without haze 2. Process the images Prof. Zou gives. 3. Write a report about this dehaze paper. The report consists of at least those parts: Background (What the paper is about, What are the shortcomings of previous papers, What problem does the paper solve...) Method (What are the steps of the algorithm What is the theory behind the algorithm...) Implement (How do you implement the algorithm, What problems do meet and how to fix them ...) Experiment (Your input images and output images) Gains (What you learn from the paper and code, What you learn from this course ...) Digital Image Process - Final Homework You are given a paper and the corresponding source code. In this paper, the author proposed an algorithm to remove the haze in an image. Figure 1. Haze removal using a single image. (a) input haze image. (b) image after haze removal by our approach. (c) our recovered depth map Paper: Single Image Haze Removal Using Dark Channel Prior Code: https://github.com/He-Zhang/image_dehaze This is the code implemented in Python, you can find other language versions in the github easily. Your tasks: 1. Try to understand the paper and code, then choose some images with haze as input, run the code to get images without haze 2. Process the images Prof. Zou gives. 3. Write a report about this dehaze paper. The report consists of at least those parts: Background (What the paper is about, What are the shortcomings of previous papers, What problem does the paper solve...) Method (What are the steps of the algorithm What is the theory behind the algorithm...) Implement (How do you implement the algorithm, What problems do meet and how to fix them ...) Experiment (Your input images and output images) Gains (What you learn from the paper and code, What you learn from this course ...)