Analysis of Cloud and Haze Removal in Remote Sensing Images Using Retinex and Wavelet Transform

By employing methods such as Retinex and wavelet transform, cloud and haze can be effectively removed from remote sensing images. The Retinex algorithm is an image dehazing approach based on brightness and color characteristics, which performs multi-scale decomposition and reconstruction to extract detailed information from images. In code implementation, this typically involves applying Gaussian filters at multiple scales to separate illumination and reflectance components. Wavelet transform analyzes high-frequency and low-frequency components of images, enabling better capture of image details and structures. This is commonly implemented using discrete wavelet transform (DWT) functions that decompose images into approximation and detail coefficients. The combination of these methods enhances the clarity and visual quality of remote sensing images, facilitating more accurate geographic information analysis and applications. Key implementation steps include proper parameter tuning for scale selection in Retinex and optimal wavelet basis selection for different image characteristics.