Image compression by using singular value decomposition with matlab simulation

Norman, Muhamad Izzat Syafiq (2022) Image compression by using singular value decomposition with matlab simulation. Project Report. Melaka, Malaysia, Universiti Teknikal Malaysia Melaka. (Submitted)

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Abstract

Network bandwidth and storage capacity are becoming increasingly constrained as the demand for multimedia products grows. That's why it's so critical to reduce redundant data and save as much storage and bandwidth as possible. Data compression, also known as source coding, is a technique used in computer science and information theory to encode information using fewer bits or other information-bearing units than an unencoded version of the same information. Because it reduces the consumption of expensive resources like memory and transmission bandwidth, compression is a cost-effective method of data storage. Singular Value Decomposition (SVD) is used as an image compression method in this research. In addition, a MATLAB programme based on Singular Value Decomposition will be created to mimic the image compression algorithm (SVD).

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