A Novel Approach of Satellite Image Enhancement Using DWT Based on 2-Type Fuzzy Logic

Abstract

This study proposes a new approach to enhance the dark and low-contrast satellite images captured under poor illumination. Images are converted from RGB to HSV color space in order to separate the Hue (H), Saturation (S), and luminance (V) components. Enhancement is achieved in saturation and luminance components using Discrete Wavelet Transform (DWT) and 2-type fuzzy logic. DWT breaks the images into high and low-frequency sub-bands and results in approximation and detailed coefficients. The approximation coefficient consists of low-frequency components, which are further modified using the 2-type Fuzzy Logic technique. Fuzzy logic is basically a point operation-based technique based on the fact that human perceived brightness characteristic is not linear. Inverse Wavelet Transform is used to achieve the enhanced saturation components. The luminance component (V) is passed through class-limited adaptive histogram equalization. All the enhanced components are then combined to get the enhanced image and finally reconverted to RGB color space. The proposed scheme significantly works well for enhancing and sharpening dark and low-contrast satellite images. The experimental results obtained by the proposed method show improved performance in terms of PSNR, MSE, mean, and variance.