Image Resolution Enhancement via Block Replacement
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Solution Overview
Problem
Conventional image editing techniques, such as cropping and enlarging, often result in pixilation and visual degradation of image quality, especially when high resolution images are cropped and resized, leading to low resolution images with blurred details.
Innovation Solution
The method involves filtering and analyzing related images to identify higher resolution blocks, which are then used to replace corresponding blocks in the cropped image, enhancing its resolution through feature extraction, matching, partitioning, and projection techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If an image is cropped and then enlarged to restore original size, then the cropped region can be focused on, but the image resolution degrades and becomes pixilated
Solution Approach 1:
The image is divided into multiple blocks, and each block is processed independently to determine whether to replace with corresponding block from related images or retain original pixels, enabling localized resolution enhancement without affecting the entire image
Solution Approach 2:
High-resolution blocks from related images are copied and pasted to replace low-resolution blocks in the cropped image, transferring detailed information from source images to enhance the resolution of the target image
2Length of stationary object
If conventional enlargement techniques are used on cropped images, then the image size is restored, but visual quality deteriorates with blurring and pixilation
Solution Approach 1:
Related images serve as intermediary sources providing high-resolution block data that mediates between the cropped low-resolution image and the desired high-resolution output, enabling quality preservation during enlargement
Solution Approach 2:
The resolution parameter of image blocks is changed by replacing low-resolution blocks with high-resolution counterparts from related images, transforming the overall image quality from low to high resolution
Data Source
AI summary
Techniques for image resolution enhancement based on data from related images are described. In one or more implementations, a cropped image and each related image from a set of the related images are divided into blocks that each include a subset of pixels. In at least some implementations, the blocks in the related images have features that match features of respective counterpart blocks in the cropped image. Then, blocks in the related images that have a relatively higher resolution than the respective counterpart blocks in the cropped image are determined. Based on this determination, one or more of the counterpart blocks in the cropped image are replaced with respective blocks from the related images to enhance the image resolution of at least a portion of the cropped image.