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A Hybrid Medical Image Compression Techniques for Lung Cancer
Objectives: This study focuses on Image compression and compares different methods. Methods/Statistical Analysis: In this work we simulated four image compression methods. The first method is focused on Karhunen-Loève Transforms (KLT), second method is focused on Walsh-Hadamard Transforms (WHT), third method based on FFT and fourth one is proposed sFFT. Findings: The experimental outcomes are compared with the different quality of parameters applying on numerous lung cancers CT scan images. The Proposed SFFT method algorithm was given better results like Peak Signal to Noise Ratio (PSNR), Structural Content (SC), Mean Square Error (MSE) and Compression Ratio (CR) are compare to other Transform methods. Application /Improvement: The Proposed SFFT technique gives improved result compared with other methods in all evaluation measures.
CR, FFT, Image Compression, KLT, Lung Cancer CT Images, MSE, PSNR, Proposed sFFT, SC, WHT.
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