Turkish Journal of Electrical Engineering and Computer Sciences




The modern communication era has led to a proliferation of digital media contents. However, the large volume of data poses difficulties because of increased bandwidth and limited storage space. Hence, this has led to the need for compression techniques. Image compression with block processing allows the coder to adapt to local image statistics and exploit the correlation present among neighboring image pixels. The main degradation factor of block transform coding is blocking artifacts (visually undesirable patterns) at high compression ratios. The degradation occurs because of coarse quantization of the transform coefficients and the independent processing of the blocks. In this paper, the novelty of the algorithm is its ability to detect and reduce the blocking artifacts using nonseparable discrete fractional Fourier transform (NSDFrFT) at high compression ratios. Three transform techniques, namely nearest neighbor interpolation, bilinear interpolation, and bicubic interpolation, were implemented. The NSDFrFT-bicubic interpolation resulted in a structurally similar high subjective quality reconstructed image with reduced blocking (for low frequency images) at high compression ratios. Simulation results are calculated with many image quality metrics such as peak signal to noise ratio, mean square error, structural similarity index, and gradient magnitude similarity measure. Evaluations, such as comparisons between the proposed and existing algorithms (DFrFT, FFT), are presented with relevant tables, graphs, and figures.


Image compression, interpolation methods, discrete fractional Fourier transform, nonseparable discrete fractional Fourier transform, compression ratios

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