# OptimizedImageEnhance **Repository Path**: Cheng_Loon/OptimizedImageEnhance ## Basic Information - **Project Name**: OptimizedImageEnhance - **Description**: Several image/video enhancement methods, implemented by Java, to tackle common tasks, like dehazing, denoising, backscatter removal, low illuminance enhancement, featuring, smoothing and etc. - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 1 - **Forks**: 0 - **Created**: 2020-04-23 - **Last Updated**: 2023-10-27 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # Fast Optimized Image/Video Enhancement Methods ![Authour](https://img.shields.io/badge/Author-Zhang%20Hao%20(Isaac%20Changhau)-blue.svg) ![](https://img.shields.io/badge/Java-1.8-brightgreen.svg) ![](https://img.shields.io/badge/OpenCV-3.2.0-brightgreen.svg) It is a set of image/video enhancement methods, implemented by Java, to tackle several common tasks, such as dehazing, denoising, underwater [backscatter](https://en.wikipedia.org/wiki/Backscatter) removal, low illuminance enhancement, featuring, smoothing and etc. **NOTE that** this repository is the integration of several repositories of Image/Video processing on [my GitHub](https://github.com/IsaacChanghau), and those standalone repositories will be **deprecated** later. - RemoveBackScatter -- **Deleted**, its zip file is available here: [[link]](/standalone_repos/RemoveBackScatter-master.zip). - OptimizedContrastEnhance -- **Deleted**, its zip file is available here: [[link]](/standalone_repos/OptimizedContrastEnhance-master.zip). - [ImageEnhanceViaFusion](https://github.com/IsaacChanghau/ImageEnhanceViaFusion) -- will be deprecated, its zip file is available here: [[link]](/standalone_repos/ImageEnhanceViaFusion-master.zip) - HazeRemovalByDarkChannelPrior -- **Deleted**, its zip file is available here: [[link]](/standalone_repos/HazeRemovalByDarkChannelPrior-master.zip) - ALTMRetinex -- **Deleted**, its zip file is available here: [[link]](/standalone_repos/ALTMRetinex-master.zip) - Image-Enhance-via-Retinex-and-DT-CWT -- **Deleted**, its zip file is available here: [[link]](/standalone_repos/Image-Enhance-via-Retinex-and-DT-CWT-master.zip) ## Description This Java project contains five different models for image/video enhancement methods as we as the MATLAB codes (in [`matlab`](/matlab/) directory) for each of them. * [ALTMRetinex](/src/main/java/com/isaac/models/ALTMRetinex.java) is inspired by [Adaptive Local Tone Mapping Based on Retinex for HDR Image](http://koasas.kaist.ac.kr/bitstream/10203/172985/1/73275.pdf), which is published by Ahn, Hyunchan. **Details and Results are shown here**: [[link]](/matlab/ALTMRetinex/). * [DarkChannelPriorDehaze](/src/main/java/com/isaac/models/DarkChannelPriorDehaze.java) is the algorithm proposed in [Single Image Haze Removal Using Dark Channel Prior](http://kaiminghe.com/publications/pami10dehaze.pdf), published by [Kaiming He](http://kaiminghe.com/). **Details and Results are shown here**: [[link]](/matlab/DarkChannelPriorDehaze/README.md). * [FusionEnhance](/src/main/java/com/isaac/models/FusionEnhance.java) is implemented according to the method described in [Enhancing Underwater Images and Videos by Fusion](http://perso.telecom-paristech.fr/~Gousseau/ProjAnim/2015/ImageSousMarine.pdf), published by Cosmin Ancuti. **Details and Results are shown here**: [[link]](/matlab/FusionEnhance/). * [OptimizedContrastEnhance](/src/main/java/com/isaac/models/OptimizedContrastEnhance.java) is implemented according to the method described in [Optimized Contrast Enhancement for Real-time Image and Video Dehazing](http://www.sciencedirect.com/science/article/pii/S1047320313000242), published by Jin-Hwan Kim. **Details and Results are shown here**: [[link]](/matlab/OptimizedContrastEnhance/). * [RemoveBackScatter](/src/main/java/com/isaac/models/RemoveBackScatter.java), Removing Backscatter to Enhance the Visibility of Underwater Object, is a fast and effective backscatter removal and enhancement method to enhance the underwater image/video as well as light hazel images. **Details and Results are shown here**: [[link]](/matlab/RemoveBackScatter/). Despite the above methods implemented in both Java and MATLAB, below contains several image enhancement and underwater restoration algorithms implemented in MATLAB (*They will be implemented in Java in the future*). * [AutomaticRedChannelRestoration](/matlab/AutomaticRedChannelRestoration.zip) is implemented on the basis of [Automatic Red-Channel Underwater Image Restoration](http://www.sciencedirect.com/science/article/pii/S1047320314001874). * [RetinexBasedRestoration](/matlab/RetinexBasedRestoration.zip) is the method proposed in [A Retinex-based Enhancing Approach for Single Underwater Image](http://smartdsp.xmu.edu.cn/memberpdf/fuxueyang/1.pdf). * [AutomaticRecoveryAtmosphericLight](/matlab/AutomaticRecoveryAtmosphericLight.zip) is the method proposed in [Automatic Recovery of the Atmospheric Light in Hazy Images](http://www.cs.huji.ac.il/~werman/Papers/iiii2013.pdf). * [DehazingCorrectionAndDecomposition](/matlab/DehazingCorrectionAndDecomposition.zip) is implemented on the basis of [Single Image Dehazing with White Balance Correction and Image Decomposition](http://ieeexplore.ieee.org/abstract/document/6411690/?reload=true). * [EnhanceViaRetinexDTCWT](/matlab/EnhanceViaRetinexDTCWT/), Image Enhancement Based on Retinex and Dual-Tree Complex Wavelet Transform, which is a efficient and effective method for enhancement of low-illuminance image/video. **Details and Results are shown here**: [[link]](/matlab/EnhanceViaRetinexDTCWT/). ## Requirements * [OpenCV](http://opencv.org/). To make the OpenCV can work with JAVA IDE, like IntelliJ or Eclipse, you may need to follow the guide of [[Install OpenCV for Java]](https://isaacchanghau.github.io/2017/04/10/Installing-OpenCV-for-Java/) to setup OpenCV. * [ImShow-Java-OpenCV](https://github.com/master-atul/ImShow-Java-OpenCV), a plain image display codes implemented by OpenCV Java version (This codes is already included in the project). ## Results ### Adaptive Local Tone Mapping Based on Retinex for HDR Image ### Image Enhancement Based on Retinex and Dual-Tree Complex Wavelet Transform ### Single Image Haze Removal Using Dark Channel Prior ### Optimized Contrast Enhancement for Real-time Image and Video Dehazing ### Enhancing Underwater Images and Videos by Fusion ### Removing Backscatter to Enhance the Visibility of Underwater Object