Enhancement Of Satellite Image Resolution With Moving Objects

Abstract

Satellite images are being used in many applications like Meteorology, Agriculture, Geology, Forestry, Landscape, Biodiversity, Planning, Education, Regional, Seismology and oceanography. The Enhanced satellite images make diagnostic details more obvious. The Image Enhancement is the main technique for improving the resolution and visual appearance of the image. One of the major issues in Image Enhancement is Wavelet Transform. The Wavelet Transform is the method which decomposes an image into a set of basic functions called Wavelets. These basis functions are limited in duration and are inherently local. A Resolution Enhancement technique is based on the Interpolation of the high-frequency subbands obtained by Discrete Wavelet Transforms (DWT). Bicubic interpolation is used as a intermediate stage for estimating high frequency components and it is more sophisticated than the nearest neighbor and bilinear techniques. The proposed technique has the advantages of superior resolution, sharper image and smoother edges. The PSNR improvement of the proposed technique is up to 7.19dB. Keywords - Image resolution, Edge detection, transforms, cycle spinning I. Introduction Image enhancement is a method of improving the definition of a video picture by a computer program, which reduces the lowest gray values to black and the highest to white, for the pictures from microscopes, surveillance cameras, and scanners. Improvement of the quality of a picture, with the aid of a computer, by giving it higher contrast or making it less blurred or less noisy. Image enhancement techniques can be divided into two broad categories are Spatial domain methods, which operate directly on pixels and frequency domain methods, which operate on the Fourier transform of an image. Interpolation in image processing is a method to increase the number of pixels in a digital image. Interpolation has been widely used in many image processing applications, such as facial reconstruction, multiple description coding, and image resolution enhancement .The interpolation-based image resolution enhancement has been used for a long time and many interpolation techniques have been developed to increase the quality of this task. Wavelets are also playing a significant role in many image processing applications. The 2-D wavelet decomposition of an image is performed by applying the 1-D discrete wavelet transform (DWT) along the rows of the image first, and then the results are decomposed along the columns. This operation results in four decomposed sub-band images referred to low-low (LL), low-high (LH), high-low (HL), and high-high (HH). The frequency components of those sub-bands cover the full frequency spectrum of the original image. A satellite image resolution enhancement technique is based on the interpolation of the high-frequency subband obtained by discrete wavelet transform (DWT) and the input image. This resolution enhancement technique uses DWT to decompose the input image into different subband. Then, the high-frequency subband images and the input low resolution image have been interpolated, followed by combining all these images to generate a new resolution enhanced image.