International Journal of Engineering and Techniques - Volume 6, Issue 2, June 2020 ISSN: 2395-1303 http://www.ijetjournal.org Page 1 Wavelet Based Various Interpolation Techniques for High Resolution Image Enhancement Processing Dr. S.Yuvaraj 1 , Dr. R.Seshasayanan 2 , Dr. K.K. Senthil Kumar 3 1(Associate Professor, Department EIE, Meenakshi College of Engineering, and Chennai, India Email: yuvarajjs@gmail.com) 2 (Professor, Department ECE, Meenakshi College of Engineering, and Chennai, India Email: se_sha_sa@yahoo.com) 3 (Associate Professor, Department ECE, Prince Shri Venkateshwara Padmavathy Engineering College, and Chennai, India Email: senthilkumar.k.k.ece@psvpec.in) I. INTRODUCTION The main objective of an image enhancement is to process a given input image so that the result is more suitable than the original image for a various application. It accentuates or sharpens image features such as edges, or curves boundaries, or contrast to make a realistic display more helpful for display the content information and analysis. The enhancement doesn't increase the natural information content of the data, but it increases the energetic range of the chosen features so that they can be detected easily. A process of image enhancing the visual quality of images due to non ideal image acquisition process (e.g., poor illumination, coarse quantization etc.) An interpolation techniques has been widely used in many image processing applications such as facial reconstruction [1], multiple description coding [2-3], and super resolution [2]–[7]. There are three well known interpolation techniques, namely nearest neighbour interpolation, bilinear interpolation, and bicubic interpolation. Bicubic interpolation is more complicated than the other two techniques and produces smoother edges. Image resolution enhancement in the wavelet domain is a relatively new research topic and recently many new algorithms have been proposed [3]–[8]. 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 the image task. Fig.1. Block diagram of one dimensional DWT filter banks – Convolution scheme. RESEARCH ARTICLE OPEN ACCESS Abstract: Satellite images are used in many fields of Earth Science Research and development. One of the main concepts of these types of images is their resolution. In this paper, we propose a hybrid satellite image resolution enhancement technique based on the image pixels values. The high-frequency content sub band’s images are obtained by the implementing SWT and DWT of the input image. In this technique the input image is decomposed into different sub band’s content images like LL, LH, HL and HH from this four different sub band’s images combined with low-resolution input image have been interpolated, followed by combining all these images to generate a new high resolution-enhanced image by using IDWT. In this way to achieve a high resolution image, an intermediate stage for estimating the high-frequency subbands has been interpolated and proposed. This proposed technique has been tested on different low resolution satellite benchmark images. The image quantitative to be analysis the PSNR, MSE, RMSE and entropy show the superiority of the proposed technique over the conventional and state-of-art image resolution enhancement techniques. Keywords — Stationary wavelet transform (SWT), discrete wavelet transform (DWT), Bicubic, Bilinear interpolation, inverse DWT, satellite image resolution enhancement, wavelet transform.