HDR Format Conversion Using Continuous Tone Mapping
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Solution Overview
Problem
Current digital media codecs are limited by dynamic range constraints, leading to visible artifacts and inefficiencies when handling high dynamic range (HDR) images, as they often require truncation or rounding operations that result in loss of data and quality issues.
Innovation Solution
The development of techniques for encoding and decoding digital media data, including HDR data, which involves forming mantissa-exponent pairs, scaling exponents, and adjusting bit lengths to compress and decompress data effectively, allowing for lossless and lossy coding while minimizing artifacts, and enabling conversion between different dynamic range formats using continuous mappings and bitstream signaling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If HDR image data with high bit depth (e.g., 32-bit float, 16-bit float) is processed, then image quality and dynamic range are improved, but device complexity and processing overhead increase
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the bit depth of HDR image data during processing. The system converts between different precision representations (32-bit float, 16-bit float, 10-bit integer, 8-bit integer) based on processing stage requirements, allowing high precision where needed while reducing complexity in other stages. This is achieved through format conversion functions that transform pixel data between different bit depths and representations.
Solution Approach 2:
The patent segments the HDR image processing pipeline into distinct stages with different precision requirements. The encoding process is divided into separate steps: initial HDR format processing, tone mapping to LDR, and final encoding. Each segment handles data at appropriate precision levels, avoiding the need to maintain high precision throughout the entire processing chain, thus reducing overall device complexity.
2Adaptability or versatility
If HDR data is converted to lower dynamic range formats, then compatibility with existing devices is improved, but image quality and dynamic range are reduced
Solution Approach 1:
The patent applies preliminary action by performing tone mapping and format conversion before the final encoding stage. The system pre-processes HDR data into intermediate formats that are optimized for subsequent processing steps. This includes converting 32-bit float HDR data to 16-bit float or 10-bit integer formats in advance, allowing compatibility with various devices while preserving quality through optimized conversion algorithms that minimize information loss.
Solution Approach 2:
The patent introduces intermediary formats as mediators between HDR and LDR representations. The system uses intermediate bit depths (16-bit float, 10-bit integer) as transition stages during conversion. These intermediary formats serve as buffers that preserve HDR quality information while being compatible with devices that cannot handle full HDR ranges, enabling gradual adaptation rather than direct conversion.
3Productivity
If simple truncation is used to reduce bit depth, then processing speed is improved, but visible artifacts and quality loss occur
Solution Approach 1:
The patent replaces the simple mechanical truncation operation with more sophisticated conversion mechanisms. Instead of directly cutting off bits, the system uses tone mapping functions and format conversion algorithms that mathematically transform the data. This substitution maintains processing efficiency while avoiding the visible artifacts caused by abrupt truncation, as the conversion processes smoothly map values between different bit depths using optimized mathematical operations.
4Adaptability or versatility
If HDR image data is processed through multiple format conversions, then adaptability to different devices is improved, but processing time and complexity increase
Solution Approach 1:
The patent applies dynamics by making the format conversion process adaptive rather than static. The system dynamically selects the appropriate conversion path based on the target device capabilities and input data characteristics. Instead of always performing the same sequence of conversions, the system adjusts the conversion strategy in real-time, choosing optimal intermediate formats and conversion methods to minimize processing time while ensuring compatibility with the destination device.
Data Source
AI summary
One or more continuous mappings are defined at a digital media encoder to convert input digital media data in a first high dynamic range format to a second format with a smaller dynamic range than the first format. The encoder converts the input digital media data to the second format with the smaller dynamic range using the continuous mapping and one or more conversion parameters relating to the continuous mapping. The encoder encodes the converted digital media data in a bitstream along with the conversion parameter(s). The conversion parameter(s) enable a digital media decoder to convert the converted digital media data back to the first high dynamic range format from the second format with the smaller dynamic range. Techniques for converting different input formats with different dynamic ranges are described.