Adaptive Digital Image Transcoding for Mobile Display Quality
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Solution Overview
Problem
Mobile communication devices often receive compressed digital images that do not meet user expectations for quality, leading to dissatisfaction due to differences in display capabilities and limited wireless communication resources.
Innovation Solution
A method that determines a mean opinion score (MoS) for digital images, transcoding them based on estimated MoS to ensure a minimum acceptable quality, adapting transcoding parameters to achieve improved image quality by comparing source and derived images across different displays and adjusting compression levels accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If digital images are compressed to conserve wireless communication resources, then transmission efficiency is improved, but image quality deteriorates
Solution Approach 1:
The system performs preliminary transcoding of digital images to multiple quality levels before transmission. The server pre-processes images and stores them in various compression formats, allowing the mobile device to select the appropriate quality level based on available wireless resources and display capabilities, thus avoiding real-time compression that would compromise quality.
Solution Approach 2:
The system dynamically adjusts transcoding parameters including compression ratio, resolution, and color depth based on the specific display characteristics of the mobile device and current wireless resource availability. By changing these parameters adaptively, the system optimizes the balance between transmission efficiency and image quality for each specific scenario.
2Adaptability or versatility
If universal transcoding standards are used, then device compatibility is improved, but image quality for specific displays deteriorates
Solution Approach 1:
The system applies local quality optimization by tailoring the transcoding parameters specifically to the characteristics of each mobile device's display. Instead of using a single universal standard, the server analyzes the target device's screen resolution, pixel density, and color capabilities to customize the image processing, ensuring optimal quality for each specific display while maintaining broad compatibility through support for multiple formats.
3Reliability
If high quality images are transmitted, then user satisfaction is improved, but wireless communication resource consumption increases
Solution Approach 1:
The system implements dynamic quality adjustment where the image transmission quality is not fixed but adapts in real-time based on the current state of wireless resources, device capabilities, and content importance. The server can dynamically select from multiple pre-encoded quality levels or adjust compression parameters on-the-fly, ensuring high user satisfaction when resources permit while conserving energy when resources are constrained.
Data Source
AI summary
A method of transcoding web images. The method comprises determining a mean opinion score (MoS) for a test source digital image, transcoding the test source digital image to a test derived digital image, and determining a MoS for the test derived digital image presented on a standard display. The method further comprises receiving a source digital image by a server computer, where the source digital image is requested by a device for presentation on a target display, transcoding the source digital image to a derived digital image by a transcoding application executed by the server computer, determining an estimated MoS for the derived digital image based on the MoS for the test source digital image, based on the MoS for the test derived digital image, and based on differences between the standard display and the target display, and changing a parameter of the transcoding application based on the estimated MoS.