Source code for book:
This repo is the implementations of the methods and algorithms introduced in the above mentioned book. If you find any errors or mistakes in the codes, or typos and tech errors in the book, feel free to open an issue to let me know. An Erratum will be maintained in this repo. Thanks for buying and reading this work, hope it be helpful for your studying or research!
-
chapter 1 Introduction
no codes in this chapter
-
chapter 2 Basics
including image transforms, histograms, color, and frequency analysis
-
chapter 3 Denoise
including classical denoising methods (Gaussian/wavelet/BM3D etc.) and DL based denoising method (DnCNN/FFDNet etc.)
-
chapter 4 Super-Resolution
including classical enhancing and DL based SR methods and network implementations (upsampling/USM and SRCNN/RCAN/EDSR etc.)
-
chapter 5 Dehazing
including dehazing methods and networks (dark channel prior, DehazeNet etc.)
-
chapter 6 HDR
including classical HDR methods and DL based networks related to HDR tasks
-
chapter 7 Composition
including alpha blending, laplacian blending and poisson blending, and image harmonization networks
example image ref: link
-
chapter 8 Enhancement
including low-light enhancement and color enhancement, retouch methods
If the content of the book helps you in your research, you can cite this book in the following format
@book{jia2024image,
title={Image algorithms for low-level vision tasks},
author={Zhuang Jia},
year={2024},
publisher={Publishing House of Electronics Industry},
isbn={9787121478765}
}
or in Chinese version as follows
@book{贾壮2024图像,
title={图像画质算法与底层视觉技术},
author={贾壮},
year={2024},
publisher={电子工业出版社},
isbn={9787121478765}
}
Due to the publisher regulations, references of the book are no longer printed in the book. Click here to see all references corresponding to the subscripts in each chapter.
- [2024-03-30] initial upload.
- [2024-06-06] book information added.
- [2024-06-18] reference and citation format added, chapter posts changed, add chinese readme