Normalized Gaussian Distributive Wavelet Transformation Based Iterated Functional Fractal Compression for Satellite Image Quality Enhancement

Authors

  • V.Sivasankar, P.Suresh Babu

DOI:

https://doi.org/10.17762/msea.v71i4.892

Abstract

Compression is a fundamental processing step in computer vision applications that efficiently stores and transmits the images while preserving the better possible quality. Satellite image compression is an essential process since the systems generate a large size of high-resolution images, which directs to higher memory requirements and higher capability of communication links. Images transmit from one device to another and the receiver gets the image with poor quality due to inefficient compression rates.  The existing compression techniques face major challenges to improve the quality of the reconstructed image with minimum time. In order to enhance the quality of the image, a novel image compression technique called Normalized Gaussian distributive continuous Wavelet Transformation based Iterated Functional Fractal Compression (NGWT-FC) technique is introduced. The main aim of the NGWT-FC technique is to perform efficient satellite image quality enhancement with a higher compression ratio. In NGWT-FC, numbers of satellite images are collected from the input database. After that, image compression is performed to minimize the storage complexity by minimizing the unrelated and unnecessary parts of the image.  First, the input satellite image is decomposed into domain and range blocks using Normalized Gaussian distributive Ricker wavelet transformation. After the decomposition, the Fractile contraction mapping between the domain and range blocks is performed using iterated function system (IFS). An IFS explains the two-dimensional set with a fixed point of Hutchinson Operator. Finally, the encoding process is performed to convert the image parts into mathematical data termed as fractal codes. After the compression, the Fractile decompression algorithm converts the encoded image into readable form. In this way, an efficient image quality enhancement is carried out with a higher compression ratio. Experimental evaluation is carried out using satellite images with different factors such as Peak signal-to-noise ratio, compression ratio, compression time, and space complexity with respect to a number of satellite images. The observed qualitative and quantitatively analyzed result confirms that the proposed NGWT-FC technique achieves higher Peak signal-to-noise ratio, compression ratio with a minimum time as well as space complexity rate than the state-of-the-art methods.

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Published

2022-09-22

How to Cite

V.Sivasankar, P.Suresh Babu. (2022). Normalized Gaussian Distributive Wavelet Transformation Based Iterated Functional Fractal Compression for Satellite Image Quality Enhancement. Mathematical Statistician and Engineering Applications, 71(4), 3309–3330. https://doi.org/10.17762/msea.v71i4.892

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Articles