Dark satellite image enhancement using knee transfer function and gamma correction based on DWT–SVD

In this paper, an improved and simple approach for enhancement of dark and low contrast satellite image based on knee function and gamma correction using discrete wavelet transform with singular value decomposition (DWT–SVD) has been proposed for quality enhancement of feature. In addition, this method can also process the high resolution dark or very low contrast images, and offers best enhanced result using tuning parameter of Gamma. The technique decomposes the input image into four frequency subbands by using DWT and estimates the singular value matrix of the low–low subband image, and then compute the knee transfer function using gamma correction for further improvement of the LL component. Afterward, processed LL band image undergoes IDWT together with the unprocessed LH, HL, and HH subbands to generate an appropriate enhanced image. Although, various histogram equalization approaches has been proposed in the literature, they tend to degrade the overall image quality by exhibiting saturation artifacts in both low- and high-intensity regions. The proposed algorithm overcomes this problem using knee function and gamma correction. The experimental results show that the proposed algorithm enhances the overall contrast and visibility of local details better than the existing techniques.