Performance Analysis of 2D-DCT based JPEG Compression Algorithm
IEEE International Conference on Applied Intelligence and Sustainable Computing (ICAISC-2023)
Abstract: Image Compression is an important process in
digital image processing, allowing for the reduction of data size
while maintaining image quality. The technique of Discrete
Cosine Transform (DCT) is commonly employed in the
compression of images, which involves transforming an image
from the spatial domain to the frequency domain. Further, the
image is quantized, and encoded. In this paper, effectiveness of
DCT for image compression is examined and the compressed
image quality is analyzed using Peak Signal-to-Noise Ratio
(PSNR) and Mean Squared Error (MSE) metrics. Results
demonstrate that DCT is an effective method for image
compression, providing high compression ratios while
maintaining reasonable image quality. Using the algorithm
discussed in this paper, for a Q-factor of 50, a compression ratio
of 26.42:1, PSNR of 31.95 dB, and MSE of 0.0007 was achieved.
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