Selective Image Blurring via Shader Code and Masking
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Solution Overview
Problem
Existing image processing applications for achieving a shallow depth of field (DOF) on mobile devices are computationally intensive and unsuitable for use on smartphones, making them inefficient for real-time image processing.
Innovation Solution
A computer system and method for selectively blurring portions of an image using shader code and a mask, allowing users to configure the mask via a touchscreen interface, which combines the original and blurred images to create a composite image with a shallow DOF effect, utilizing a blur engine, mask engine, and effects engine to generate a composite image with an unblurred and blurred portion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional post-processing techniques are used to achieve shallow depth of field, then the DOF effect is achieved, but the computational intensity becomes too high for mobile devices
Solution Approach 1:
The image processing is segmented into two passes: a first pass that processes only the background region to generate a blurred background, and a second pass that processes the foreground region. This segmentation reduces the total computational load compared to processing the entire image, while still achieving the desired shallow DOF effect.
Solution Approach 2:
The patent applies blurring processing selectively to only the background portion of the image rather than the entire image. By performing partial action on the background region that requires blurring, the computational intensity is reduced while maintaining the effectiveness of the shallow DOF effect in the final composite image.
2Reliability
If existing image processing applications process the entire image, then the blurring effect is applied, but the processing time increases significantly
Solution Approach 1:
The image is divided into foreground and background regions, with blurring applied only to the background in the first pass. This segmentation strategy reduces processing time by avoiding redundant computations on the foreground region that does not require blurring, while still achieving the desired blurring effect in the final output.
3Reliability
If more expensive equipment is used, then shallow depth of field can be achieved, but the cost increases
Solution Approach 1:
The patent replaces the mechanical/optical system (expensive camera equipment with physical aperture control) with a computational system (image processing algorithms). By using software-based image processing to simulate shallow DOF effects, the need for expensive specialized equipment is eliminated, making the technology accessible on standard mobile devices.
Data Source
AI summary
Image processing includes: applying shader code to an original image to generate a blurred image version (BIV); obtaining a composite image that is generated based at least in part on the original image and the BIV, wherein the composite image is generated by: obtaining a mask that includes an unblurred region and a blurred region; applying the mask to combine the original image and the BIV to render a composite image that includes an unblurred portion comprising a portion of the original image corresponding to the unblurred region of the mask, and a blurred portion comprising a portion of the BIV corresponding to the blurred region of the mask; and outputting the composite image to be displayed.


