Prasad, Talari Jayachandra
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Image compression and reconstruction using improved Stockwell transform for quality enhancement Babu, Padigala Prasanth; Prasad, Talari Jayachandra; Soundararajan, Kadambi
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i2.pp1583-1593

Abstract

Image compression is an important stage in picture processing since it reduces the data extent and promptness of image diffusion and storage, whereas image reconstruction helps to recover the original information that was communicated. Wavelets are commonly cited as a novel technique for image compression, although the production of waves proceeding smooth areas with the image remains unsatisfactory. Stockwell transformations have been recently entered the arena for image compression and reconstruction operations. As a result, a new technique for image compression based on the improved Stockwell transform is proposed. The discrete cosine transforms, which involves bandwidth partitioning is also investigated in this work to verify its experimental results. Wavelet-based techniques such as multilevel Haar wavelet, generic multiwavelet transform, Shearlet transform, and Stockwell transforms were examined in this paper. The MATLAB technical computing language is utilized in this work to implement the existing approaches as well as the suggested improved Stockwell transform. The standard images mostly used in digital image processing applications, such as Lena, Cameraman and Barbara are investigated in this work. To evaluate the approaches, quality constraints such as mean square error (MSE), normalized cross-correlation (NCC), structural content (SC), peak noise ratio, average difference (AD), normalized absolute error (NAE) and maximum difference are computed and provided in tabular and graphical representations.