Image Block Sorting and Compression for Storage Reduction
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Solution Overview
Problem
Large and high-quality graphical digital images consume significant computer storage and bandwidth, and existing image compression methods often result in either large file sizes or significant image degradation.
Innovation Solution
The technique involves rearranging and sorting image blocks based on their variation values and color values to apply varying levels of compression, allowing for a higher compression ratio while maintaining image quality, by subdividing images into blocks, analyzing their pixel data, and reorganizing them into new images for efficient compression using algorithms like JPEG.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional image compression algorithms (JPEG) are applied to individual images, then file size is reduced, but image quality degrades significantly
Solution Approach 1:
The patent divides images into multiple blocks and processes them separately, allowing different compression levels to be applied to different regions. This segmentation enables preserving quality in important areas while achieving higher compression in less critical areas, resolving the contradiction between file size reduction and image quality maintenance.
Solution Approach 2:
The patent applies variable compression quality to different blocks within an image based on their importance and characteristics. Critical regions (such as faces or important objects) receive higher quality compression, while less important regions receive lower quality compression, thus achieving overall file size reduction without significant degradation of perceived image quality.
2Quantity of substance
If high-level JPEG compression is applied, then file size decreases, but image quality is lost
Solution Approach 1:
The patent performs preliminary analysis of image blocks to identify their characteristics and importance before applying compression. This preliminary action allows the system to pre-determine which blocks can tolerate higher compression and which require quality preservation, thereby minimizing information loss while achieving file size reduction.
Solution Approach 2:
The patent dynamically adjusts compression parameters (such as quantization tables and compression ratios) based on the characteristics of each image block. By changing these parameters adaptively, the system achieves higher compression ratios in suitable blocks while maintaining quality in blocks where information loss would be detrimental.
3Manufacturing precision
If low-level JPEG compression is applied, then image quality is maintained, but file size reduction is minimal
Solution Approach 1:
By segmenting the image into multiple blocks, the patent can apply low-level (high quality) compression only to critical blocks that require quality preservation, while applying higher compression to non-critical blocks. This selective approach maintains overall image quality while achieving significant file size reduction, resolving the contradiction between quality maintenance and file size reduction.
4Quantity of substance
If conventional archiving techniques are used on image collections, then storage space is reduced, but compression ratio is limited
Solution Approach 1:
The patent merges multiple individual image compression processes into a unified block-based approach that processes images from a collection simultaneously. By extracting, analyzing, and compressing blocks from multiple images in a coordinated manner, the system achieves higher overall compression ratios and better storage space utilization compared to conventional independent image archiving techniques.
Data Source
AI summary
Embodiments herein include an image manager that provides for image compression by rearranging an order of blocks from one or more images and then sorting and writing those blocks into one or more different images. This technique enables using a high-level of image compression to reduce a relatively large amount of pixels to a common subset of values than would ordinarily be possible with the original image(s). This can include extracting a plurality of blocks from a graphical digital image file. Each block from the graphical digital image file can be a group of pixels. The image manager analyzes each block to produce a corresponding variation value for each of the blocks, indicating a level of variation of pixel data within a respective block. The image manager sorts blocks according to the variation values, and can apply a level of image compression to each respective block, based on the variation value and/or average color of each respective block, to compress each respective block. For a given image or set of images, certain techniques disclosed herein can yield an image archive having a file size that is about two to four times smaller than conventional archiving techniques applied to the same given image or set of images.