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MATLAB implementation of the algorithm in the paper "Low-Light Image Enhancement with Semi-Decoupled Decomposition". IEEE TRANSACTIONS ON MULTIMEDIA.1 IntroductionLow-light image enhancement is important for highquality image display and other visual applications. It is a non-trivial task, as the enha...
原始的图像是正常光照下的,论文这里是采用matlab中的-imadjust将图像进行伽马非线性调暗。 进行伽马调暗的公式如下: 当γ小于1时,图片变亮; 当γ等于1时,图片不变; 当γ大于1时,图片变暗。 为了模拟自然拍摄情况下低质量的图片,图像数据进行了添加高斯噪音的处理。这里使用MATLAB中的imnoise实现。 高斯噪音处理公...
When an image is captured in low-light, it gets the low visibility. To overcome the low visibility of the image, some operations are to be performed. But in this paper, image enhancement is introduced using illumination mapping. First, R, G, B maximum values in each pixel of the ...
In experiments, we evaluated SSN and other low-light image enhancement methods on two low-light traffic image sets: the Berkeley Deep Drive (BDD) dataset and the Hong Kong night-time multi-class vehicle (HK) dataset. The results indicated that SSN significantly improves upon other methods in ...
Low light imaging and low light image enhancement have wild applications in our daily life and different scientific research fields, like night surveillance, automated driving, fluorescence microscopy, high speed imaging and so on. However, there is still a long way to go in dealing with these ...
We implement all experiments using MATLAB R2018b on a PC with an Intel(R) Core(TM) i5-7300HQ CPU @2.50 GHz processor. Conclusion Existing low-light image enhancement algorithms cannot satisfactorily maintain the detail and colour information when processing images with complex backgrounds. Therefore...
Therefore, we propose a novel lightweight network for low-light image enhancement named RGB-Net. Firstly, unlike traditional Retinex-based models, our approach leverages the separation of RGB color channels to enhance the input image. Each RGB channel is independently enhanced for brightness and ...
This manuscript introduces an innovative multi-stage image fusion framework that adeptly integrates infrared (IR) and visible (VIS) spectrum images to surmount the difficulties posed by low-light settings. The approach commences with an initial preproces
Code for our paper "A Bio-Inspired Multi-Exposure Fusion Framework for Low-light Image Enhancement" The code for the comparison method is also provided, seelowlight Downloads:google Drive(Just unzip data to current folder) DatasetsVV, LIME, NPE, NPE-ex1, NPE-ex2, NPE-ex3, DICM, MEF ...