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Project Title: Comparison of Methods Used in Lossy Digital Image Compression
Henry, Joseph
Henry, Joseph
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Tunyan, Knarik
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2020
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4662_joseph.henry.pdf
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This project explores the need for lossy image compression methods to analyze what information is lost when compressing images. For digital images, compression is particularly important because depending on how you change or alter an image can impact its quality. Digital images in their raw form require an enormous amount of storage capacity. Considering the important role played by digital imaging, it is necessary to develop a system that produces a high degree of compression while preserving critical image information. There are various lossy transformation techniques used for data compression. The Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) are the two most commonly used transformations. In this research project, Google Colab and MATLAB were used to examine and compare the differences between the JPEG and JPEG 2000 compression algorithm. This project also examines which transforms compact the most energy(or information) in an image.
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