An Image Compression Method Based on Subspace and Downsampling
Yazarlar (1)
Doç. Dr. Serkan KESER Kırşehir Ahi Evran Üniversitesi, Türkiye
Makale Türü Açık Erişim Özgün Makale (Ulusal alan endekslerinde (TR Dizin, ULAKBİM) yayınlanan tam makale)
Dergi Adı Bitlis Eren üniversitesi fen bilimleri dergisi
Dergi ISSN 2147-3129
Dergi Tarandığı Indeksler TR DİZİN
Makale Dili İngilizce Basım Tarihi 03-2023
Cilt / Sayı / Sayfa 12 / 1 / 215–225 DOI 10.17798/bitlisfen.1225312
Makale Linki https://doi.org/10.17798/bitlisfen.1225312
Özet
In this study, a new Karhunen-Loeve transform based algorithm with acceptable computational complexity is developed for lossy image compression. This method is based on obtaining an autocorrelation matrix by clustering the highly correlated image rows obtained by applying downsampling to the image. The KLT is applied to the blocks created from the downsampled image using the eigenvector (or transform) matrix obtained from the autocorrelation matrix; thus, the transform coefficient matrices are obtained. Then these coefficients were compressed by the lossless coding method. One of the proposed method’s essential features is sufficient for a test image to have one transform matrix, which has low dimensional. While most image compression studies using PCA (or KLT) in the literature are used in hybrid methods, the proposed study presents a simple algorithm that only downsamples images and applies KLT. The proposed method is compared with JPEG, BPG, and JPEG2000 compression methods for the PSNR-HVS and the SSIM metrics. In the results found for the test images, the average PSNR-HVS and SSIM results of the proposed method are higher than JPEG, very close to JPEG2000, and lower than BPG. It has been observed that the proposed method generally gives better results than other methods in images containing low-frequency components with high compression ratios.
Anahtar Kelimeler
Image compression | Downsampling | Transform coefficient matrix | KLT
BM Sürdürülebilir Kalkınma Amaçları
Atıf Sayıları
Google Scholar 3
An Image Compression Method Based on Subspace and Downsampling

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