Shared Dictionary Image Compression for Graphics Remoting
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Solution Overview
Problem
There is a lack of efficient data compression mechanisms to improve network traffic and processing efficiency in desktop virtualization environments, where graphics remoting systems transmit similar images repeatedly, leading to inefficiencies in data transmission and processing.
Innovation Solution
The implementation of a shared dictionary in graphics remoting systems that encodes sequences of pixels in images by referencing similar sequences from previously transmitted images, allowing for efficient compression and decompression of images using hashing and image window management to reduce network traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If images are transmitted repeatedly in graphics remoting systems, then visual representation is maintained, but network traffic increases and processing efficiency decreases
Solution Approach 1:
The patent combines multiple similar images into a single compressed representation by identifying and merging common pixel sequences. The shared dictionary stores unique image sequences once, and subsequent similar images reference these stored sequences, reducing redundant data transmission while maintaining visual representation continuity.
Solution Approach 2:
The patent creates compressed copies of image data by storing unique sequences in a shared dictionary and referencing them multiple times. Instead of transmitting full image copies, the system transmits references to previously stored sequences, significantly reducing network traffic while preserving the ability to reconstruct complete images at the client side.
2Measurement precision
If full images are transmitted repeatedly, then image quality is maintained, but processing efficiency at the client decreases
Solution Approach 1:
The patent segments images into sequences of pixels and identifies common segments across multiple images. By dividing images into manageable sequences and storing only unique segments in the shared dictionary, the system maintains complete image quality for reconstruction while reducing the processing load through selective storage and referencing of segments.
3Loss of energy
If a shared dictionary is implemented for image compression, then network traffic is reduced, but system complexity increases
Solution Approach 1:
The shared dictionary serves multiple functions: it stores unique image sequences, provides compression references for subsequent images, and enables both compression and decompression operations. This multi-functionality reduces the need for separate compression and decompression mechanisms, managing system complexity while achieving significant network traffic reduction.
Data Source
AI summary
A method and system for data compression of images using a shared dictionary are described herein. According to one embodiment, a server identifies a current images that is part of a stream of images generated by an application hosted by the server. The stream of images includes images previously transmitted to the client. For each segment of pixels in the current image, the server searches a dictionary containing data for the stream of images. If the dictionary includes data corresponding to the segment of pixels in the current image, the server determines metadata for the segment of pixels in the current image using the corresponding data from the dictionary, and transmits the metadata to the client without transmitting the segment of pixels from the current image.