Dynamic Image Quality Degradation for Storage Management
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Solution Overview
Problem
The banking and other industries face significant challenges in managing large image data storage sizes, leading to increased storage requirements, slow image retrieval, high operational costs, and transmission inefficiencies due to the use of lossy compression techniques and batch processing methods.
Innovation Solution
A system and method that recursively degrades image quality based on reduction criteria to reduce storage size, allowing for extended online image availability, reduced communication costs, and increased transmission speed, while maintaining access to high-quality images for verification purposes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If lossy compression techniques (e.g., JPEG) are used to reduce image storage size, then storage requirements are reduced, but vital document information may be lost
Solution Approach 1:
The system dynamically adjusts image quality based on time elapsed since document creation. Recently created documents are stored at high quality, while older documents are progressively degraded to lower quality over time. This dynamic approach allows the system to maintain information integrity when needed while reducing storage requirements for less critical historical data.
Solution Approach 2:
The invention changes the quality parameter of images based on their age and access patterns. By adjusting the compression level and quality settings according to temporal parameters and usage frequency, the system optimizes the balance between storage efficiency and information preservation without applying uniform lossy compression to all documents.
2Duration of action of moving object
If high-quality images are maintained online for extended periods, then customer access is improved, but data storage requirements increase significantly
Solution Approach 1:
The system implements dynamic quality adjustment where images are stored at high quality initially and then progressively degraded over time. This allows recent documents to remain accessible at full quality while older documents occupy less storage space, enabling extended online availability without linearly increasing storage requirements.
Solution Approach 2:
The invention applies periodic quality reduction to images based on time intervals. At predetermined intervals, image quality is reduced in a controlled manner, allowing the system to maintain an extended inventory of online images while managing storage growth through systematic, periodic degradation rather than continuous high-quality storage.
3Quantity of substance
If batch processing is used to retrieve older images from archive, then storage costs are reduced, but retrieval time increases significantly
Solution Approach 1:
The system performs preliminary actions by maintaining reduced-quality versions of images in online storage in advance. When customers need to view older documents, the lower-quality versions are already available for immediate access, eliminating the need for time-consuming batch processing and archive retrieval while still providing acceptable viewing quality.
Solution Approach 2:
The invention creates lower-quality, shorter-lived online versions of images that serve as disposable proxies for the full-resolution archived images. These reduced-quality images are sufficient for most customer viewing needs and can be generated or maintained at lower cost, providing quick access without requiring expensive fast-archive retrieval mechanisms.
4Loss of information
If lossless compression methods are used to reduce storage size, then document information is preserved, but compression complexity increases
Solution Approach 1:
The system changes compression parameters dynamically based on image age and importance. Instead of using complex lossless compression for all images, the system adjusts compression settings to apply lighter compression to recent, important documents and heavier compression to older, less critical images. This parameter-based approach simplifies the overall system by avoiding uniformly complex lossless compression while preserving information where necessary.
Data Source
AI summary
A system and method for managing image storage size. The invention uses reduction criteria to determine how much to reduce the storage size of an image over time. In one embodiment, reduction of data storage size includes degrading the quality of the image. The reduced-size image replaces the image from the previous iteration. The smaller storage allows longer access to the information in quick access storage and quicker transmission time.