Image Compression Quality Optimization via PSNR Targeting
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Solution Overview
Problem
Conventional image compression techniques struggle to simultaneously achieve optimal image quality and reduce file size, especially when adjusting image quality settings, as increasing quality settings may not guarantee better image quality and can lead to increased file sizes, particularly for encoded data.
Innovation Solution
A method using a processor to determine an optimal image quality value based on a target peak signal-to-noise ratio (PSNR) within a set image quality range, which involves encoding the image at multiple quality values, calculating the PSNR, and iteratively adjusting the quality range to find a value that satisfies the target PSNR, thereby optimizing image compression quality and reducing file size.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If image quality setting is increased to improve compression quality, then image quality is improved, but file size increases
Solution Approach 1:
The patent applies parameter changes by transforming the image quality setting from a subjective quality scale to an objective PSNR-based parameter. The system calculates PSNR values for different quality settings and uses these objective parameters to determine the optimal quality value that achieves the desired compression quality while minimizing file size. This parameter transformation enables precise control and optimization of the compression-quality trade-off.
2Ease of manufacture
If conventional encoding is used to compress images, then processing is simple, but optimal quality and file size reduction cannot be simultaneously achieved
Solution Approach 1:
The patent implements feedback by calculating the PSNR value after encoding and using this feedback to determine whether the current quality setting is optimal. The system compares the actual PSNR with the target PSNR and adjusts the quality setting accordingly. This feedback mechanism enables the system to automatically optimize compression quality while controlling file size, resolving the contradiction between simplicity and optimization precision.
3Manufacturing precision
If iterative encoding is performed to find optimal quality, then compression quality is optimized, but processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating PSNR values for different quality settings and storing them in a lookup table before actual compression. During encoding, the system only needs to query the pre-calculated PSNR values rather than performing iterative encoding calculations in real-time. This preliminary computation significantly reduces processing time while maintaining quality optimization precision.
Data Source
AI summary
Disclosed are methods, apparatuses, systems, and/or non-transitory computer readable media for improving/optimizing image compression quality settings. A method of compressing an input image, using at least one processor, includes verifying a desired compression quality value desired for compressing the input image, determining an optimal image quality value that corresponds to a target peak signal-to-noise ratio (PSNR) from a set image quality range based on the desired compression quality value, and outputting an image file encoded at the optimal image quality value as a compressed file of the input image.