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Complex wavelet transform and singular value decomposition based image contrast enhancement

机译:基于复小波变换和奇异值分解的图像对比度增强

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In this work, we have proposed a new image contrast enhancement technique based on complex wavelet transform (CWT) and singular value decomposition (SVD). The technique decomposes the input image into the eight frequency subbands by using CWT and estimates the singular value matrix of the real and complex low-low subbands, and then it reconstructs the enhanced image by applying the inverse CWT (ICWT). The technique is compared with the conventional image equalization techniques such as standard general histogram equalization (GHE) and local histogram equalization (LHE), as well as state-of-art technique such as Brightness Preserving Dynamic Histogram Equalization (BPDHE) and singular value equalization (SVE). The experimental results are showing the superiority of the proposed method over the conventional and the state-of-art techniques.
机译:在这项工作中,我们提出了一种基于复数小波变换(CWT)和奇异值分解(SVD)的新图像对比度增强技术。该技术通过使用CWT将输入图像分解为八个频率子带,并估计实数和复杂的低-低子带的奇异值矩阵,然后通过应用逆CWT(ICWT)重构增强的图像。将该技术与常规图像均衡技术(例如标准通用直方图均衡(GHE)和局部直方图均衡(LHE))以及最新技术(例如亮度保持动态直方图均衡(BPDHE)和奇异值均衡)进行了比较。 (SVE)。实验结果表明,所提出的方法优于传统技术和先进技术。

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