Implement -Single Image Haze Removal Using Dark Channel Prior 張瀚元
Single Image Haze Removal using Dark Channel Prior Kaiming He, Jian Sun, and Xiaoou Tang IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2009 (Oral)
Outline Goals of Haze Removal Technical description Implement References and Appendix
Goals of Haze Removal
Technical description Haze Imaging Model Dark Channel Estimating the transmission Soft Matting Guided Image Filtering
Haze Imaging Model I = J * t + A * ( 1 – t ) I : The observed intensity J : The scene radiance t : the medium transmission describing the portion of the light that is not scattered and reaches the camera.
Haze Imaging Model (cont) I = J * t + A * ( 1 – t ) d = - β ln t d : depth
Dark Channel 何愷明經由統計後發現,自然界中的物體, 其 RGB 值中必有一值偏低 一張由 影像之 min ( r, g, b ) 構成的圖被稱為 該影像之 Dark Channel
Dark Channel (cont)
: color channel of J : dark channel of J
Dark Channel (cont)
Estimating the transmission
Soft Matting matting Laplacian matrix : Refined transmission map : Transmission map before refined
Soft Matting(cont) A Closed Form Solution to Natural Image Matting by Anat Levin 優點 : 較夠找到清晰的輪闊 缺點 : 計算 matting Laplacian matrix 與之後的矩 陣運算時間複雜度太高 本實作用 Guided Image Filtering 來取代 soft matting 部份
Guided Image Filtering Kaiming He, Jian Sun, and Xiaoou Tang The 11th European Conference on Computer Vision (ECCV), 2010 (Oral)
Guided Image Filtering(cont)
優點 : 時間複雜度低 實作容易 缺點 : 跟 matting Laplacian matrix 的結果相 比較不精細
Implement 程式流程 Methods of operation Result Limit Demo
程式流程
Methods of operation
Result Canon3.mp Remove haze resultOptimal dark channel map
Result(cont) train.bmp train.bmp 除霧 Dark channel
Result(cont) tiananmen1.bmp tiananmen1.bmp 除霧 Dark channel
Limit Inherently white or grayish objects Haze imaging model is invalid for some image
Demo Demo.avi Youtube link :
References and Appendix Single Image Haze Removal using Dark Channel Prior Kaiming He, Jian Sun, and Xiaoou Tang A Closed Form Solution to Natural Image Matting Anat Levin Dani Lischinski Yair Weiss Guided Image Filtering Kaiming He, Jian Sun, and Xiaoou Tang