Spatial analytics techniques: A comparative analysis of FFT, DCT, and Wavelet-based image compression on Kaggle Rose images
Shalabi, Shefaa Khawfani, Ruba
Shalabi, Shefaa
Khawfani, Ruba
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Date
2026-01-17
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Abstract
This chapter presents a comprehensive comparative analysis of three widely used transform-based image compression techniques: Fast Fourier Transform (FFT), Discrete Cosine Transform (DCT), and Wavelet Transform. The compression transforms are tested under three threshold settings. Utilizing a dataset of 497 JPEG images from Kaggle, we systematically evaluated each method under three distinct threshold settings to examine their performance. The ROSE images dataset was chosen due to its abundant edges and intricate details, effectively distinguishing the differences between compressed images. Setting A employed the highest threshold value, resulting in minimal compression. Setting B had an intermediate threshold value, while Setting C utilized the lowest threshold value, leading to maximum compression. Lower threshold values discard more coefficients, thereby increasing the compression ratio, but potentially affecting image quality.
The evaluation metrics used in this study include Mean Squared Error (MSE), Pea
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Effat University
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Mathematical Modeling for Big Data Analytics