Satellite image resolution and brightness enhancement using discrete, stationary wavelet and singular value decomposition

Satellite images are used in the field of research and video processing applications. One of the main issues of satellite image interpretation is its low resolution. Resolution is defined as the smallest number of discriminable detail in an image. There are two types of resolution, grey level resolution and spatial resolution. Grey level resolution enhances the smallest discriminable details in an image, i.e. we can discriminate change in grey level. Images are being processed in order to obtain more enhanced resolution. The proposed image resolution enhancement technique is based on high frequency sub-band images obtained by discrete wavelet transform (DWT) of the input image. First of all interpolate the input image using bicubic interpolation then perform DWT on the interpolated input image to obtain different sub-bands. The high frequency subband's edges are enhanced using stationary wavelet (SWT). Combine these two high frequency subband's which are modified and interpolated. Then perform inverse DWT (IDWT) to get high resolution image. To increase the brightness of an image, use SVD (singular value decomposition) and DWT. The quantitative and visual results are showing the superiority of the proposed technique.