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

被引:88
作者
Bhandari, A. K. [1 ]
Soni, V. [1 ]
Kumar, A. [1 ]
Singh, G. K. [2 ]
机构
[1] PDPM Indian Inst Informat Technol Design & Mfg, Jabalpur 482011, India
[2] Indian Inst Technol Roorkee, Dept Elect Engn, Uttrakhand 247667, India
关键词
Adaptive learning; CS algorithm; Wavelet thresholding; DWT-SVD; Image equalization and remote sensing; image contrast enhancement; SINGULAR-VALUE DECOMPOSITION; THRESHOLDING NEURAL-NETWORK; MEDICAL ULTRASOUND IMAGES; WAVELET DOMAIN; RESOLUTION ENHANCEMENT; HISTOGRAM EQUALIZATION; NOISE-REDUCTION; COLOR IMAGES; TRANSFORM; SIGNAL;
D O I
10.1016/j.isatra.2014.04.007
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
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. (C) 2014 ISA. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:1286 / 1296
页数:11
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