Inter-Frame Residual Super-Resolution for Lower Image Processing Load

Solution Overview

Problem

Current super-resolution display apparatuses face high computation costs and large computation amounts due to the need for full super-resolution processing on images, which is inefficient and resource-intensive.

Innovation Solution

An image processing method that utilizes inter-frame residuals to identify target pixel regions for super-resolution processing and updates other pixel regions using previously processed frames, reducing the need for full super-resolution processing on the entire image.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If full super-resolution processing is performed on the entire image, then display quality is improved, but computation amount and computation costs increase significantly

Engineering Contradiction:

Improvedisplay qualityVSAvoidcomputation amount

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The image is divided into multiple blocks, and super-resolution processing is selectively applied only to blocks containing moving objects rather than the entire image. This segmentation approach maintains display quality for important regions while reducing overall computation amount by excluding static regions from intensive processing.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Different processing strategies are applied to different regions of the image based on their characteristics. Moving object blocks receive full super-resolution processing to ensure quality, while static blocks use simpler interpolation methods, achieving local optimization of both quality and computation efficiency.

Inventive Principle:

Principle #3Local quality

2Manufacturing precision

If full super-resolution processing is performed on the entire image, then display quality is improved, but computation costs increase significantly

Engineering Contradiction:

Improvedisplay qualityVSAvoidcomputation costs

Core Design Contradiction:

Manufacturing precisionVSUse of energy by moving object

Solution Approach 1:

The image is divided into multiple blocks, and super-resolution processing is selectively applied only to blocks containing moving objects rather than the entire image. This segmentation approach maintains display quality for important regions while reducing overall computation amount by excluding static regions from intensive processing.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Instead of applying super-resolution processing to the entire image, the method applies partial processing only to necessary regions (moving object blocks). This partial action approach reduces computation costs while maintaining sufficient display quality for dynamic content that requires attention.

Inventive Principle:

Principle #16Partial or excessive action

3Device complexity

If selective super-resolution processing is applied only to moving object blocks, then computation amount is reduced, but processing speed must be maintained for real-time performance

Engineering Contradiction:

Improvecomputation amountVSAvoidprocessing speed

Core Design Contradiction:

Device complexityVSSpeed

Solution Approach 1:

Motion detection and block classification are performed in advance to identify which blocks require super-resolution processing. This preliminary action allows the system to prepare processing targets before applying intensive computation, optimizing processing speed by avoiding unnecessary processing of static blocks while maintaining real-time performance.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The image is divided into multiple blocks, and super-resolution processing is selectively applied only to blocks containing moving objects rather than the entire image. This segmentation approach maintains display quality for important regions while reducing overall computation amount by excluding static regions from intensive processing.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentEP4036854B1Image processing method and apparatus, and electronic device

Publication Date: 2026.04.22 HUAWEI TECH CO LTD

Figure 1
Figure 2
Figure 3~4

AI summary

The present invention discloses an image processing method and apparatus, and an electronic device, and pertains to the field of image processing. The method includes: obtaining an inter-frame residual between two adjacent image frames to obtain a residual block; determining, based on the residual block, a target pixel region on which super-resolution processing needs to be performed; and performing super-resolution processing on only the target pixel region to obtain a target pixel region after the super-resolution processing. For another pixel region, a super-resolution processing result of an image frame that is in the two image frames and on which super-resolution processing is performed is directly used. This application can resolve a problem of high computation costs of super-resolution processing.