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Cuckoo search algorithm based satellite image contrast and brightness enhancement using DWT-SVD

机译:使用DWT-SVD基于布谷鸟搜索算法的卫星图像对比度和亮度增强

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摘要

This paper presents a new contrast enhancement approach which is based on Cuckoo Search (CS) algorithm and DWT-SVD for quality improvement of the low contrast satellite images. The input image is decomposed into the four frequency subbands through Discrete Wavelet Transform (DWT), and CS algorithm used to optimize each subband of DWT and then obtains the singular value matrix of the low-low thresholded subband image and finally, it reconstructs the enhanced image by applying IDWT. The singular value matrix employed intensity information of the particular image, and any modification in the singular values changes the intensity of the given image. The experimental results show superiority of the proposed method performance in terms of PSNR, MSE, Mean and Standard Deviation over conventional and state-of-the-art techniques.
机译:本文提出了一种新的对比度增强方法,该方法基于杜鹃搜索(CS)算法和DWT-SVD来改善低对比度卫星图像的质量。通过离散小波变换(DWT)将输入图像分解为四个频率子带,并使用CS算法优化DWT的每个子带,然后获得低-低阈值子带图像的奇异值矩阵,最后重构出增强的通过应用IDWT获得图像。奇异值矩阵使用了特定图像的强度信息,并且奇异值的任何修改都会更改给定图像的强度。实验结果表明,相对于传统技术和最新技术,该方法在PSNR,MSE,均值和标准差方面的性能优越。

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