Gradient Image Detection for Display Power Savings
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Solution Overview
Problem
Existing display power saving methodologies often degrade image quality for gradient images, leading to user dissatisfaction and the disabling of power saving features, as there is no automatic technique for detecting gradient images.
Innovation Solution
The implementation of a gradient image detection system that identifies gradient images by analyzing pixel intensity variations and smoothness, allowing for the inhibition of contrast enhancement techniques that cause banding artifacts, thereby preserving image quality and enabling continued power saving on non-gradient images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If contrast enhancement techniques are applied to save display power, then power consumption is reduced, but image quality deteriorates for gradient images due to banding artifacts
Solution Approach 1:
The gradient detection algorithm performs preliminary analysis of the image content before applying contrast enhancement techniques. By detecting gradient regions in advance, the system can selectively apply or inhibit contrast enhancement in specific areas, preventing banding artifacts while maintaining power savings in non-gradient regions.
Solution Approach 2:
The patent applies different processing strategies to different regions of the image based on gradient detection. Gradient regions are identified and treated differently from non-gradient regions, allowing contrast enhancement to be applied only where it won't cause banding artifacts, thus maintaining local image quality while achieving overall power savings.
2Manufacturing precision
If contrast enhancement is inhibited to maintain image quality on gradient images, then image quality is preserved, but power savings are reduced
Solution Approach 1:
Instead of completely inhibiting contrast enhancement across the entire image, the patent applies partial action by selectively applying contrast enhancement only to non-gradient regions. This partial application maintains image quality in gradient areas while still achieving power savings in the remaining non-gradient portions of the image.
Solution Approach 2:
The system applies different power management strategies to different image regions: contrast enhancement is inhibited in gradient regions to preserve quality, while it is applied in non-gradient regions to achieve power savings. This localized approach resolves the contradiction by making the treatment spatially variable rather than uniform.
3Manufacturing precision
If power saving features are disabled to avoid image quality degradation, then image quality is maintained, but overall power efficiency decreases
Solution Approach 1:
The patent implements a dynamic power management approach where the contrast enhancement technique is adaptively enabled or disabled based on real-time gradient detection. The system continuously analyzes image content and adjusts its power saving strategy accordingly, maintaining image quality when gradients are detected while achieving power savings when they are not, thus optimizing overall power efficiency.
Solution Approach 2:
The gradient detection algorithm provides feedback about image content characteristics to the power management system. This feedback loop allows the system to make informed decisions about whether to apply contrast enhancement, ensuring that power saving actions do not degrade image quality while maximizing overall power efficiency through adaptive control.
Data Source
AI summary
Systems, apparatus, articles of manufacture, and methods are disclosed for gradient image detection to improve power savings. An example disclosed apparatus includes programmable circuitry to at least one of instantiate or execute the machine readable instructions to identify a region in an image that satisfies a brightness threshold, define a plurality of lines in the image that extend away from the region, and determine the region corresponds to a gradient based on an analysis of pixels along different ones of the plurality of lines.