Abstract
The Joint Picture Expert Group (JPEG) committee has been standardizing next-generation image compression, called JPEG XL, to meet the specific needs for a responsive web, wide color gamut, and high dynamic range. JPEG XL supports lossy and lossless compression. A variable-sized discrete cosine transform (DCT) block is used for lossy compression. A block partitioning method is regarded as a critical function for the performance of JPEG XL. The current DCT block partitioning method used in JPEG XL is highly dependent on the compression rate and tends to assign small-sized DCT blocks to homogeneously textured regions (HTRs) having similar or regular patterns. We propose a region-adaptive DCT block partitioning method that assigns larger blocks to the HTR. The proposed method identifies the HTRs by using a combined metric employing a sum-modified Laplacian, zero-crossing, and colorfulness metric for measuring the region homogeneity. Objective, subjective, and visual comparison evaluations with the ten images recommended by the JPEG working group were provided to show the improvement in coding performance. The proposed method shows its superiority in terms of the compression efficiency evaluated using six objective metrics, subjective tests with 15 participants, visual comparison improvements in the HTR, and gains in the execution time.
Highlights
With the advent of modern information and communication technology, millions of images are generated by mobile phones and digital cameras, uploaded, and shared through various applications such as cloud services and social networking services
We propose a more efficient and regionadaptive block partitioning method that improves the encoding performance of the current Joint Picture Expert Group (JPEG) XLM based on the features that allow humans to perceive a better image quality
EXPERIMENTAL RESULTS We evaluated the performance of the proposed block partitioning method compared with state-of-the-art JPEG XL block partitioning
Summary
With the advent of modern information and communication technology, millions of images are generated by mobile phones and digital cameras, uploaded, and shared through various applications such as cloud services and social networking services. With an increase in the recent demand for supporting massive images, such as 360-degree and high-dynamic range (HDR) images, an image compression format with better coding performance is needed for a band-limited network transmission of images. To address this demand, the JPEG committee has begun developing the next-generation image coding standard, JPEG XL (ISO/IEC 18181) in March 2019 [2].
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