New Transforms for JPEG Format
This work addresses image compression efficiency for users of JPEG format, but it is incremental as it builds on existing transforms without introducing a new paradigm.
The paper tackled the problem of improving JPEG image compression by analyzing alternative transforms to replace the DCT, finding that the local cosine transform outperforms DCT at low bitrates and the discrete wavelet transform matches DCT at high bitrates.
The two-dimensional discrete cosine transform (DCT) can be found in the heart of many image compression algorithms. Specifically, the JPEG format uses a lossy form of compression based on that transform. Since the standardization of the JPEG, many other transforms become practical in lossy data compression. This article aims to analyze the use of these transforms as the DCT replacement in the JPEG compression chain. Each transform is examined for different image datasets and subsequently compared to other transforms using the peak signal-to-noise ratio (PSNR). Our experiments show that an overlapping variation of the DCT, the local cosine transform (LCT), overcame the original block-wise transform at low bitrates. At high bitrates, the discrete wavelet transform employing the Cohen-Daubechies-Feauveau 9/7 wavelet offers about the same compression performance as the DCT.