Multi-Resolution Image Brightness Correction and Noise Suppression

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Solution Overview

Problem

Existing image processing techniques for correcting backlit images, such as HDR, amplify noise and generate halos, especially in environments with limited calculation resources like FPGA, making it difficult to produce clear output images without significant computational overhead.

Innovation Solution

An image processing method that generates multi-resolution images, calculates brightness correction amounts based on lowest resolution images and edge information, and suppresses noise using inter-adjacent resolution differential images, allowing for effective brightness correction with reduced computational cost.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Illumination intensity

If HDR processing is applied to correct backlit images, then brightness correction is improved, but noise amplification occurs

Engineering Contradiction:

Improvebrightness correctionVSAvoidnoise amplification

Core Design Contradiction:

Illumination intensityVSObject-affected harmful factors

Solution Approach 1:

The image is divided into multiple local areas, and each area is processed separately with its own brightness correction amount calculated based on local luminance characteristics. This segmentation allows noise suppression to be applied selectively in different regions while maintaining brightness correction effectiveness.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Different processing strategies are applied to different local areas based on their specific characteristics. The brightness correction amount and noise suppression strength are adjusted locally rather than uniformly across the entire image, optimizing both brightness correction and noise control for each region.

Inventive Principle:

Principle #3Local quality

2Object-affected harmful factors

If noise suppression processing is introduced in HDR processing, then noise amplification is suppressed, but calculation cost increases

Engineering Contradiction:

Improvenoise amplification suppressionVSAvoidcalculation cost

Core Design Contradiction:

Object-affected harmful factorsVSDevice complexity

Solution Approach 1:

Noise suppression is applied partially rather than uniformly across the entire image. The processing focuses on local areas where noise is most problematic, using simplified calculations for brightness correction that reduce the overall computational burden while still achieving effective noise suppression where needed.

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The patent uses computationally efficient algorithms that provide sufficient noise suppression without requiring expensive, complex processing. The brightness correction amount is calculated using straightforward luminance-based methods rather than computationally intensive techniques, achieving acceptable results with lower calculation costs.

Inventive Principle:

Principle #27Cheap short-living objects (Disposable)

3Device complexity

If linear low-pass filter is used in illumination light component estimation, then calculation cost is reduced, but halo generation occurs

Engineering Contradiction:

Improvecalculation costVSAvoidhalo generation

Core Design Contradiction:

Device complexityVSObject-affected harmful factors

Solution Approach 1:

The brightness correction amount is calculated separately for each local area based on its specific luminance characteristics. This local processing approach allows the system to maintain edges more effectively in different regions, reducing halo generation around boundaries while keeping calculation costs manageable through localized rather than global processing.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The patent calculates brightness correction amounts based on luminance information before final image composition. By preparing correction data in advance at the local area level, the system can apply corrections more efficiently and reduce artifacts like halos that occur when correction is applied too late in the processing pipeline.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS10438323B2Image brightness correction and noise suppression method, device, and recording medium for storing image processing program

Publication Date: 2019.10.08 NEC CORP

AI summary

The present invention provides an image processing method, an image processing device, and an image processing program which require low computing costs and with which it is possible to minimize noise amplification and halo generation caused by HDR. An image processing device according to one embodiment of the present invention has: a multi-resolution image generation means for generating a multi-resolution image; a correction amount calculation means for calculating a brightness correction amount on the basis of a lowest-resolution image of the multi-resolution image, a differential image between adjacent resolutions of the multi-resolution image, and edge information calculated at each resolution of the multi-resolution image; and a noise suppression means for calculating, on the basis of the lowest-resolution image, the differential image between adjacent resolutions, the edge information, and the brightness correction amount, an image after brightness correction in which a noise component is suppressed.