Bhandari A K, Soni V, Kumar A, Singh G K
PDPM Indian Institute of Information Technology Design and Manufacturing, Jabalpur 482011, MP, India.
Department of Electrical Engineering, Indian Institute Technology Roorkee, Uttrakhand 247667, India.
ISA Trans. 2014 Jul;53(4):1286-96. doi: 10.1016/j.isatra.2014.04.007. Epub 2014 Jun 2.
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.
本文提出了一种基于布谷鸟搜索（CS）算法和离散小波变换-奇异值分解（DWT-SVD）的新的对比度增强方法，用于提高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，使用CS算法对DWT的每个子带进行优化，然后获得低低阈值子带图像的奇异值矩阵，最后通过应用逆离散小波变换（IDWT）重建增强图像。奇异值矩阵利用了特定图像的强度信息，奇异值的任何修改都会改变给定图像的强度。实验结果表明，与传统技术和现有技术相比，该方法在峰值信噪比（PSNR）、均方误差（MSE）、均值和标准差方面具有优越的性能。
