Multi-view Image Coding Region-based Illumination Correction

Solution Overview

Problem

Existing multi-view image coding methods face inefficiencies due to increased code amounts from illumination and color compensation parameters, particularly when dealing with localized mismatches between cameras, which cannot be adequately addressed by single correction parameters.

Innovation Solution

The method divides images into areas, estimates correction parameters from adjacent coded/decoded frames to correct illumination and color mismatches, reducing the need for additional encoding and enabling localized correction without increasing the code amount.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If illumination compensation and color correction parameters are added to correct mismatches between cameras, then the accuracy of prediction is improved, but the code amount increases

Engineering Contradiction:

Improveprediction accuracyVSAvoidcode amount

Core Design Contradiction:

Measurement precisionVSQuantity of substance

Solution Approach 1:

The image is divided into multiple regions, and correction parameters are estimated separately for each region. This allows localized correction of illumination and color mismatches without applying correction globally, thereby reducing the overall number of parameters that need to be encoded while maintaining prediction accuracy in each specific region.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Different correction parameters are applied to different regions of the image based on local characteristics. The correction parameter estimation unit estimates parameters specific to each region's illumination and color conditions, enabling precise local correction without increasing global code amount, as only region-specific parameters are encoded.

Inventive Principle:

Principle #3Local quality

2Quantity of substance

If single correction parameters are used for illumination and color compensation, then the code amount is reduced, but the ability to handle localized mismatches deteriorates

Engineering Contradiction:

Improvecode amountVSAvoidlocalized correction capability

Core Design Contradiction:

Quantity of substanceVSAdaptability or versatility

Solution Approach 1:

The image is divided into multiple regions, and correction parameters are estimated separately for each region. This allows localized correction of illumination and color mismatches without applying correction globally, thereby reducing the overall number of parameters that need to be encoded while maintaining prediction accuracy in each specific region.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Different correction parameters are applied to different regions of the image based on local characteristics. The correction parameter estimation unit estimates parameters specific to each region's illumination and color conditions, enabling precise local correction without increasing global code amount, as only region-specific parameters are encoded.

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS8532411B2Multi-view image coding method, multi-view image decoding method, multi-view image coding device, multi-view image decoding device, multi-view image coding program, and multi-view image decoding program

Publication Date: 2013.09.10 NIPPON TELEGRAPH & TELEPHONE CORP

AI summary

In the disclosed multi-view image encoding/decoding method in which a frame to be encoded/decoded is divided and encoding/decoding is done to each region, first, a prediction image is generated not only for the region to be processed, but also for the already encoded/decoded regions neighboring to the region to be processed. The prediction image is generated using the same prediction method for both kinds of regions. Next, correction parameters for correcting illumination and color mismatches are estimated from the prediction image and decoded image of the neighboring regions. At this time, the estimated correction parameters can be obtained even at the decoding side, therefore, encoding them is unnecessary. Thus, by using the estimated correction parameters to correct the predicted image that was generated for the region to be processed, a corrected predicted image that can be actually used is generated.