Image Decoder Post-Processing Using Encoding Metadata
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Solution Overview
Problem
Conventional methods for creating high-quality portable video bitstreams face challenges such as increased power costs, heat dissipation, storage capacity issues, and quality versus bit rate compromises, particularly at low bit rates, and lack effective post-processing using pre-processing and encoding information.
Innovation Solution
A method for image decoding that utilizes pre-processing and encoding information to perform post-processing, including up-sampling and adaptive filtering, allowing for improved image quality and lower bit rate encoding by using meta-data and statistical information from image capture and encoding processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional compression methods are used to create low bit rate video, then bit rate is reduced, but image quality deteriorates
Solution Approach 1:
The system performs preliminary actions during encoding by capturing and storing pre-processing information (noise reduction parameters, sharpening filters, color space conversions) and encoding statistics (quantization parameters, transform coefficients) before the actual decoding. This allows the decoder to perform intelligent post-processing that compensates for compression artifacts, thereby maintaining image quality at low bit rates without requiring high bit rate streams
Solution Approach 2:
The system implements feedback by using encoding statistics and pre-processing information stored during encoding to guide the post-processing operations during decoding. The decoder receives feedback about how the image was processed and encoded, allowing it to reverse the effects of compression and restore image quality, effectively creating a closed-loop system that maintains quality across the entire processing chain
2Manufacturing precision
If recording at full capture resolution is performed, then image quality is maintained, but power consumption and heat dissipation increase
Solution Approach 1:
The system applies partial action by performing image processing operations selectively rather than uniformly across the entire image. During encoding, only necessary pre-processing steps are applied, and during decoding, post-processing is applied only to regions or features that benefit from enhancement. This allows the system to maintain image quality while reducing computational workload and power consumption compared to processing every pixel at full resolution throughout the entire pipeline
3Quantity of substance
If hybrid compression technologies are used, then bit rate is reduced, but quality versus bit rate compromise occurs
Solution Approach 1:
The system changes parameters dynamically by adjusting encoding and decoding parameters based on the specific characteristics of the image content and the available bit rate. The encoder adapts quantization parameters, transform types, and pre-processing strength based on image complexity. The decoder then reverses these parameter changes using stored encoding statistics, allowing the system to optimize the quality-bit rate trade-off for each specific encoding scenario rather than using fixed hybrid compression parameters
Data Source
AI summary
A method for image decoding is disclosed. The method generally includes the steps of (A) receiving from a medium (1) an encoded signal and (2) transform data comprising at least one of (i) encoding statistics embedded in the encoded signal, (ii) encoding information and (iii) pre-processing information, wherein (a) the encoding statistics are created by an encoder in encoding an intermediate input signal to create the encoded signal, (b) the encoding information is producible by the encoder in the encoding and (c) the pre-processing information is producible by a pre-processor in converting an image input signal into the intermediate input signal, (B) generating an intermediate output signal by decoding the encoded signal and (C) generating an image output signal by processing the intermediate output signal in response to the transform data.