Implement -Single Image Haze Removal Using Dark Channel Prior

601410103 張瀚元

Single Image Haze Removal using Dark Channel PriorKaiming 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 intensityJ : The scene radiancet : 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)

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)

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 result Optimal 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 : http://youtu.be/PpaBcgurDpY

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 FilteringKaiming He, Jian Sun, and Xiaoou Tang