Data-independent Low-complexity KLT Approximations for Image and Video Coding
This work addresses the problem of enabling real-time KLT application in image and video coding standards like JPEG and HEVC, though it appears incremental.
The paper tackled the high computational cost and input-dependence of the Karhunen-Loève transform (KLT) in image and video coding by proposing low-complexity approximations, demonstrating their suitability for compression through extensive experiments.
The Karhunen-Loève transform (KLT) is often used for data decorrelation and dimensionality reduction. The KLT is able to optimally retain the signal energy in only few transform components, being mathematically suitable for image and video compression. However, in practice, because of its high computational cost and dependence on the input signal, its application in real-time scenarios is precluded. This work proposes low-computational cost approximations for the KLT. We focus on the blocklengths $N \in \{4, 8, 16, 32 \}$ because they are widely employed in image and video coding standards such as JPEG and high efficiency video coding (HEVC). Extensive computational experiments demonstrate the suitability of the proposed low-complexity transforms for image and video compression.