Block-Based Tone Curve Generation for Image Contrast

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Solution Overview

Problem

Existing image processing technologies struggle to effectively improve image quality, particularly in managing dynamic range and maintaining contrast across varying brightness levels.

Innovation Solution

An information processing device that acquires first and second tone curves, divides image data into blocks, determines representative values, and generates a third tone curve for each block by mixing the first and second tone curves based on the representative values. The device then applies correction values to target pixels based on the third tone curve of the target block and a different block.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If a single tone curve is used for the entire image, then processing is simple and fast, but contrast and dynamic range management deteriorate in images with wide brightness variations

Engineering Contradiction:

Improveprocessing speedVSAvoidimage quality

Core Design Contradiction:

ProductivityVSManufacturing precision

Solution Approach 1:

The image is divided into multiple blocks, and a separate tone curve (third tone curve) is generated for each block based on local representative values. This segmentation allows each block to have optimized contrast and dynamic range management while maintaining overall processing efficiency through localized operations rather than pixel-by-pixel processing.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Different tone curves are applied to different blocks of the image based on local brightness characteristics. The third tone curve for each block is generated by mixing first and second tone curves according to the block's representative value, enabling local adaptation to varying brightness conditions while preserving global processing efficiency.

Inventive Principle:

Principle #3Local quality

2Manufacturing precision

If block-based processing is implemented, then local contrast and dynamic range improve, but processing complexity increases

Engineering Contradiction:

Improveimage qualityVSAvoidprocessing complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The image is pre-divided into blocks and representative values are calculated for each block before tone curve generation. This preliminary organization of data into blocks with aggregated representative values simplifies subsequent tone curve application and reduces the complexity of processing individual pixels, making the block-based approach more efficient.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The tone curve parameters are dynamically adjusted for each block based on local representative values. By changing the tone curve parameters locally rather than globally, the system achieves improved image quality while maintaining manageable complexity through parameter adaptation rather than structural complexity.

Inventive Principle:

Principle #35Parameter changes

3Manufacturing precision

If tone curves are generated for each block, then local brightness management improves, but computational load increases

Engineering Contradiction:

Improvebrightness managementVSAvoidcomputational load

Core Design Contradiction:

Manufacturing precisionVSUse of energy by moving object

Solution Approach 1:

The image is segmented into blocks, and tone curve generation is performed only at the block level rather than for each pixel. This segmentation reduces computational load by aggregating pixel information into representative block values, enabling efficient local brightness management without the prohibitive cost of per-pixel processing.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Tone curve parameters are changed and optimized for each block based on representative values, achieving local brightness management efficiency. By changing parameters at the block level rather than pixel level, the system reduces computational load while maintaining effective local brightness control.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20250045889A1Information processing device, information processing method, and information processing program

Publication Date: 2025.02.06 FUJIFILM CORP

AI summary

An information processing device performs processing on image data to be input. The information processing device includes: a processor configured to: acquire a first tone curve and a second tone curve; divide the image data into a plurality of blocks and determine a representative value for each block; generate a third tone curve for each block based on the first tone curve, the second tone curve, and the representative value; and determine a correction value to be applied to a target pixel based on the third tone curve of a target block including the target pixel and the third tone curve of a block different from the target block.