Iterative Scanline Decompression for Low-Memory Image Rendering
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Solution Overview
Problem
Decompressing and displaying compressed images is computationally expensive for devices with limited resources, such as mobile devices with low memory or processing capabilities, leading to potential rendering failures and high memory consumption.
Innovation Solution
Implementing an enhanced decompression approach that iteratively decompresses and downscales compressed images on a scanline-by-scanline basis, dynamically adjusting the downscaling factor based on the original and target resolutions, and using techniques like averaging or filtering to reduce memory usage without affecting image fidelity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the entire compressed image is decompressed at once, then the complete image is available for processing, but memory consumption increases significantly
Solution Approach 1:
The patent divides the image into individual scanlines and processes them separately through the decompression pipeline. Each scanline is decompressed, downsampled, and rendered independently, allowing the system to handle images with limited memory by processing one scanline at a time rather than loading the entire image into memory simultaneously.
2Quantity of substance
If downscaling is applied to reduce memory usage, then memory consumption decreases, but image fidelity may be affected
Solution Approach 1:
The patent applies downsampling immediately after decompression of each scanline, before the data is stored or processed further. This preliminary downsampling reduces the memory footprint early in the pipeline while preserving essential image quality through proper interpolation algorithms, preventing memory exhaustion before it becomes a critical issue.
3Manufacturing precision
If traditional decompression methods are used, then image quality is maintained, but processing time and computational resources increase
Solution Approach 1:
By segmenting the decompression process into independent scanline operations, the system can process multiple scanlines in parallel or efficiently pipeline the operations. This reduces total processing time compared to traditional methods that must process the entire image sequentially, while maintaining image quality through consistent application of the decompression algorithm to each scanline.
Data Source
AI summary
Enhanced decompression of compressed images, in which a decompressed image with a target resolution is assembled using an iteratively decompressed and downscaled quantity of scanlines of a compressed image, the quantity of scanlines correlating to a downscaling factor determined based on an original resolution of the compressed image and the target resolution.