Adaptive Dither Bitstream for Truncation Error Image Compression
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Solution Overview
Problem
Current compression techniques are ineffective in mitigating visual artifacts produced during the compression/decompression process for images and other data types.
Innovation Solution
A method involving a truncation process for data associated with display processing, image processing, or data processing, which generates truncated data, computes truncation error values, generates residual samples, and creates a bitstream based on these samples and error values. This bitstream is then used to reconstruct the original data with reduced errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If lossy bandwidth compression is applied to reduce data transmission, then bandwidth efficiency is improved, but visual artifacts and image reproduction accuracy deteriorate
Solution Approach 1:
The patent applies preliminary dithering before truncation and preliminary error calculation before compression. By adding dither noise to the original image data before truncation, the patent prevents banding artifacts from forming during compression. The error values are calculated in advance and encoded into the bitstream, allowing the decoder to reconstruct images with significantly reduced visual artifacts while maintaining bandwidth efficiency.
Solution Approach 2:
The patent introduces dither noise as an intermediary element between the original image and the compressed representation. This dither noise acts as a mediator that randomizes quantization errors, preventing them from forming visible banding patterns. Additionally, error values serve as intermediaries that carry correction information from encoder to decoder, enabling accurate reconstruction without transmitting the full original image data.
2Productivity
If truncation process is used for bandwidth compression, then data transmission efficiency is improved, but visual artifacts increase
Solution Approach 1:
The patent converts the harmful effect of truncation-induced quantization errors into a beneficial outcome by intentionally adding dither noise before truncation. This dither noise transforms the deterministic banding artifacts that would normally result from truncation into randomized noise patterns that are visually less noticeable. The truncation process, which would normally create harmful banding, is thus converted into a beneficial compression mechanism when combined with dithering.
Solution Approach 2:
The patent changes the parameter distribution of the image data by adding dither noise, which modifies the statistical characteristics of the pixel values. This parameter change ensures that after truncation, the quantization errors are distributed more uniformly rather than forming concentrated banding patterns. The error values are also transformed and encoded in a specific format suitable for efficient transmission in the bitstream.
3Manufacturing precision
If dithering is applied to reduce visual artifacts, then image quality is improved, but computational complexity increases
Solution Approach 1:
The patent applies dithering with locally adaptive parameters rather than uniform global parameters. The dither strength and error encoding are tailored to local image characteristics, allowing computational resources to be focused where they are most needed. This local adaptation improves image quality in critical regions while avoiding unnecessary computation in areas where simple truncation suffices, thus balancing quality improvement with computational complexity management.
Data Source
AI summary
Systems, devices, apparatus, and methods, including computer programs encoded on storage media, for truncation error signaling and adaptive dither for lossy bandwidth compression are described. A processor may perform a truncation process for data, where the data is associated with display processing, image processing, or the data processing, where the truncation process for the data results in truncated data. The processor may compute a set of truncation error values associated with the truncation process for the truncated data. The processor may generate a set of residual samples for the truncated data. The processor may generate a bitstream based on the set of residual samples for the truncated data and the set of truncation error values associated with the truncation process.