Study on Compression Methods for Quality Enhancement with Satellite Images
  IJCTT-book-cover
 		          
 
© 2022 by IJCTT Journal
Volume-70 Issue-10
Year of Publication : 2022
Authors : V. Sivasankar, P. Suresh Babu
DOI :  10.14445/22312803/IJCTT-V70I10P101

How to Cite?

V. Sivasankar, P. Suresh Babu, "Study on Compression Methods for Quality Enhancement with Satellite Images," International Journal of Computer Trends and Technology, vol. 70, no. 10, pp. 1-7, 2022. Crossref, https://doi.org/10.14445/22312803/IJCTT-V70I10P101

Abstract
Image processing is an essential technique for transforming an image into digital form for performing certain operations to attain useful information. Satellite image processing is an essential area in research and development with earth and satellite images taken by artificial satellites. The photographs are gathered in digital form and processed by computers to extract the information. Image enhancement increases the quality and information content before processing. Image compression is an essential step for processing large images through an encoder. Image pre-processing is carried out to improve image quality by minimizing undesired distortions for a particular application. Image segmentation is the method of dividing the digital image into multiple segments to enhance image quality. Many researchers carried out their research on image compression, pre-processing, and segmentation methods for image quality enhancement. But, the compression ratio and compression time were not improved by image quality enhancement. In order to address these problems, many image compression and filtering techniques are reviewed.

Keywords
Image compression, Information, Pre-processing, Segmentation, Satellite image processing.

Reference

[1] Alex Golts and Yoav Y. Schechner, "Image Compression Optimized for 3D Reconstruction by Utilizing Deep Neural Networks", Journal of Visual Communication and Image Representation, Elsevier, pp. 1-16, 2021.
[2] Chong Chen, Yong-Liang Li and Lidong Huang, "An Entropy Minimization Histogram Emergence Scheme and Its Application in Image Compression," Signal Processing: Image Communication, Elsevier, vol. 99, pp. 1-15
[3] Ali Can Karaca, Ozan Kara and Mehmet Kemal Gullu, "Multitempgan: Multitemporal Multispectral Image Compression Framework Using Generative Adversarial Networks," Journal of Visual Communication and Image Representation, Elsevier, vol. 81, pp. 1-18, 2021.
[4] Zixi Wang, Guiguang Ding, Jungong Han and Fan Li, "Deep Image Compression with Multi-Stage Representation," Journal of Visual Communication and Image Representation, Elsevier, vol. 79, pp. 1-15, 2021.
[5] Ramen Pal, Somnath Mukhopadhyay, Debasish Chakraborty and Ponnuthurai Nagaratnam Suganthan, "Very High-Resolution Satellite Image Segmentation Using Variable-Length Multi-Objective Genetic Clustering for Multi-Class Change Detection," Journal of King Saud University – Computer and Information Sciences, Elsevier, pp. 1-13, 2022.
[6] Muhammad Alam, Jian-Feng Wang, Cong Guangpei, LV Yunrong and Yuanfang Chen, "Convolutional Neural Network for the Semantic Segmentation of Remote Sensing Images," Mobile Networks and Applications, Springer, vol. 26, pp. 200–215, 2021.
[7] Javed Iqbal and Mohsen Ali, "Weakly-Supervised Domain Adaptation for Built-Up Region Segmentation in Aerial and Satellite Imagery," ISPRS Journal of Photogrammetry and Remote Sensing, Elsevier, vol. 167, pp. 263-275, 2020.
[8] Zhe Jiang, Wenchong He, Marcus Stephen Kirby, Arpan Man Sainju, Shaowen Wang, Lawrence V. Stanislawski, Ethan J Shavers and E. Lynn Usery, "Weakly Supervised Spatial Deep Learning for Earth Image Segmentation Based on Imperfect Polyline Labels," ACM Transactions on Intelligent Systems and Technology, vol. 13, no. 2, pp. 1–20, 2022.
[9] Huajin Li, Yusen He, Qiang Xu, Jiahao Deng, Weile Li and Yong Wei, "Detection and Segmentation of Loess Landslides Via Satellite Images: A Two?Phase Framework," Landslides, Springer, vol. 19, pp. 673 – 686, 2022.
[10] Simo Thierry, Welba Colince, Ntsama Eloundou Pascal and Noura Alexendre, "Shock Filter Coupled with a High-Order PDE for Additive Noise Removal and Image Quality Enhancement," Array, Elsevier, vol.12, pp. 1-18, 2021.
[11] C. Arunachalaperumal and S. Dhilipkumar "An Efficient Image Quality Enhancement Using Wavelet Transform," Materials Today: Proceedings, Elsevier, vol. 24, no. 3, pp. 2004-2010, 2020.
[12] Hafsa Ouchra, Abdessamad Belangour, Allae Erraissi, "A Comparative Study on Pixel-Based Classification and Object-Oriented Classification of Satellite Image," International Journal of Engineering Trends and Technology, vol. 70, no. 8, pp. 206-215, 2022. Crossref, https://doi.org/10.14445/22315381/IJCTT-V70I8P221.
[13] Qinglan Fan, Ying Bi, Bing Xue and Mengjie Zhang, "Genetic Programming for Feature Extraction and Construction in Image Classification," Applied Soft Computing, Elsevier, vol. 118, pp. 1-18, 2022.
[14] Haoliang Yuan, Junyu Li, Loi Lei Lai, and Yuan Yan Tang, "Low-Rank Matrix Regression for Image Feature Extraction and Feature Selection," Information Sciences, Elsevier, vol. 552, pp. 214-226, 2022.
[15] Huafei Yu, Tinghua Ai, Min Yang, Lina Huang and Jiaming Yuan, "A Recognition Method for Drainage Patterns Using A Graph Convolutional Network," International Journal of Applied Earth Observations and Geoinformation, Elsevier, vol. 107, pp. 1-15, 2022.
[16] Mamata Wagh, Pradipta Kumar Nanda, "Rough Set and Otsu Approach Based Hybrid Image Classification Under Uneven Lighting Conditions," International Journal of Engineering Trends and Technology, vol. 69, no. 12, pp. 92-102, 2021. Crossref, https://doi.org/10.14445/22315381/IJCTT-V69I12P211.
[17] Rashedul Islam, Md. Rafiqul Islam and Kamrul Hasan Talukder, "An Efficient ROI Detection Algorithm for Bangla Text Extraction and Recognition From Natural Scene Images," Journal of King Saud University–Computer and Information Sciences, Springer, vol. 79, pp. 20107–20132, 2020.
[18] B. Vidhya and R. Vidhyapriya, "Image Compression and Reconstruction by Examplar Based Inpainting Using Wavelet Transform on Textural Regions," Cluster Computing, Springer, vol. 22, pp. 8335–8343, 2019.
[19] Mohammed M. Siddeq and Marcos A. Rodrigues, "A Novel High-Frequency Encoding Algorithm for Image Compression," EURASIP Journal on Advances in Signal Processing, Springer, vol.2017, no. 26 , pp. 1-15, 2017.
[20] P.Svoboda,M.Hradis, D.Barina and P.Zemcik, "Compression Artifacts Removal Using Convolutional Neural Networks,” Journal of WSCG, vol.24, no.2 , pp.63-72.
[21] Atif Nazir,Rehan Asharf and Taiha Hamdani, "Content Based Image Retrieval System by Using HSV Color Histogram, Discrete Wavelet Transform and Edge Histogram Descriptor," 2018.
[22] F.Artuger, F.Ozkaynak, Fractal, "Image Compression Method for Lossy Data Compression," International Conference on Artificial Intelligence and Data Processing 2018.
[23] Y.Vishnu Tej, M. James Stephen, PVGD. Prasad Reddy, Praveen Choppala, "A Novel Methodology for Denoising Impulse Noise in Satellite Images Through Isolated Vector Median Filter with K-Means Clustering," International Journal of Engineering Trends and Technology, vol. 70, no. 8, pp. 272-283, 2022. Crossref, https://doi.org/10.14445/22315381/IJCTT-V70I8P229.
[24] Yumo Zhang, Zhanchuan Cai, "A New Image Compression Algorithm Based on Non-Uniform Partition and U-System," IEEE Transaction on Multimedia, vol. 23, 2021.
[25] Chandresh K Parmer and Prof.Kruti Pancholi, “A Review on Image Compression Techniques," Journal of Information, Knowledge and Research in Electrical Engineering.
[26] Gaurva Vijayvriya, Dr.Sanjay Silakari, Dr.Rajeev Pandey," A Survey: Various Techniques of Image Compression," International Journal of Computer Science and Information Security, vol. 11, no.10.
[27] Jagadish H. Pujar and Lohit M. Kadlaskar, "A New Lossless Method of Image Compression and Decompression Using Huffman Coding Techniques," JATIT - Journal of Theoretical and Applied Information Technology, pp. 18-22, 2012.
[28] Wencheng Wang, Zhenxue Chen, Xiaohui Yuan and Xiaojin Wu, "Adaptive Image Enhancement Method for Correcting Low-Illumination Images," Information Sciences, Elsevier, vol. 496, pp. 25-41, 2019.