Image Defogging with Retinex Algorithms
Single-Scale Retinex Algorithm (SSR), Multi-Scale Retinex Algorithm (MSR), and Multi-Scale Retinex with Color Restoration Algorithm (MSRCR) - Implementation and Technical Analysis
Tarel and Hautiere's Image Dehazing Methods
Implementation of Tarel and Hautiere's image dehazing algorithms, featuring excellent haze removal results with significant reference value for research purposes, including practical code implementation details.
MATLAB Implementation of Image Dehazing Algorithm
This program implements image haze removal based on the paper "Single Image Haze Removal Using Dark Channel Prior" - complete with source code and implementation details
Dark Channel Prior Algorithm for Image Dehazing
MATLAB Implementation of Dark Channel Prior Algorithm for Effective Image Dehazing
Image Defogging Using Guided Filtering
Code for image defogging based on guided filtering, downloaded from Dr. Kaiming He's homepage, implementing edge-preserving image enhancement.
Image Dehazing for Foggy Conditions Using Wavelet Transform Method
Implement enhanced image dehazing using wavelet transform method for superior visual clarity in fog-affected images, with practical code implementation approaches
Image Dehazing Using Curvelet Transform and Gaussian Inverse Filtering
MATLAB implementation of image dehazing algorithm employing Curvelet transform and Gaussian inverse filtering techniques, including performance visualization results
Image Dehazing Based on RETINEX Theory
Image dehazing implementation using RETINEX theory, primarily processes 2D images with broad applicability across most image types, featuring code-oriented algorithm explanations
Research Papers on Dark Channel Prior-Based Image Dehazing
Best Paper award at CVPR 2009 - He Kaiming's seminal work on dark channel prior-based image dehazing, including associated papers, presentation materials, and MATLAB implementation. The dark channel prior represents a statistical observation of haze-free images: in most local image patches, at least one color channel contains pixels with very low intensity values. This principle enables direct estimation of haze concentration from a single input image and recovery of high-quality dehazed results through optimized atmospheric scattering modeling and transmission map calculations.
Image Defogging Using Multi-Scale Retinex Algorithm
Implementation of image defogging based on multi-scale Retinex algorithm. Code is tested and ready to run, effectively removing haze while preserving original image colors through multi-scale Gaussian filtering and color restoration techniques.