Adaptive Video Compression Circuit System for Scene Complexity
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Solution Overview
Problem
Conventional MJPEG video compression technologies use a fixed compression rate, leading to poor adaptability across varying scenes, resulting in issues such as stuck frames or dropped video quality due to inadequate adjustment to scene complexity.
Innovation Solution
An adaptive compression rate method that adjusts based on the complexity of images by analyzing statistical data from adjacent frames, using a digital signal processor to determine the necessary compression rate through quantization table scale adjustments, ensuring optimal visual quality while meeting bandwidth limitations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed compression rate is used for MJPEG video compression, then the computation complexity and computing power requirements are kept low, but the adaptability to various scenes deteriorates, causing stuck frames in complex scenes or quality loss in simple scenes
Solution Approach 1:
The patent implements dynamic adjustment of the quantization table scale based on the complexity degree of video frames. The system transitions from a fixed compression rate to a dynamic one by calculating complexity metrics (such as variance of gradient modulus) for each frame and adjusting the quantization scale accordingly. This allows the compression rate to adapt to scene complexity while maintaining manageable computational complexity through efficient algorithms.
Solution Approach 2:
The patent changes the parameter of quantization table scale dynamically based on frame complexity. By modifying this key parameter according to calculated complexity degrees, the system achieves adaptability to different scenes without requiring complex computational structures. The complexity degree itself becomes a controllable parameter that drives the adjustment of compression settings.
2Productivity
If a high compression rate is applied to simple scenes, then the bandwidth utilization is improved, but the video definition deteriorates due to excessive compression
Solution Approach 1:
The patent applies different compression rates to different frames based on their individual complexity characteristics. Simple frames receive higher compression rates (larger quantization scale) while complex frames receive lower compression rates (smaller quantization scale). This localized quality adjustment ensures optimal bandwidth utilization without sacrificing video definition where it matters most.
Solution Approach 2:
The system applies compression selectively based on frame complexity. For simple frames, it applies stronger compression (excessive action relative to complexity) to maximize bandwidth utilization. For complex frames, it applies milder compression to preserve quality. This partial application of compression strength prevents overall quality degradation while maintaining good bandwidth utilization.
3Manufacturing precision
If a low compression rate is used for complex scenes, then the video quality is maintained, but the bandwidth consumption increases and may cause frame loss
Solution Approach 1:
The patent maintains high video quality selectively for complex frames by applying lower compression rates only where needed. For simple frames, it uses higher compression rates to reduce bandwidth consumption. This localized quality preservation ensures that bandwidth-critical complex scenes maintain definition while overall bandwidth usage is optimized across the entire video sequence.
Solution Approach 2:
The system applies mild compression (partial action) only to complex frames where quality preservation is critical, while applying stronger compression to simple frames. This selective approach prevents bandwidth exhaustion and frame loss in complex scenes without unnecessarily compromising quality in simple scenes, achieving an optimal balance between quality and bandwidth consumption.
Data Source
AI summary
A method for compressing video signals based on adaptive compression rate and a circuit system thereof are provided. In the method, a digital signal processor is used to process a video so as to frame-by-frame obtain statistical data, for example, a maximum of compressed data. The maximum of compressed data of a previous frame is used to determine a compression state of a current frame. The compression state of the frame allows the processor to decide a direction to adjust a compression ratio. Next, statistical data of the previous frame is used to decide a stride to adjust the compression ratio. The statistical data can be a maximum of compressed data and a quantization table scale referred to rendering a prediction curve that allows the processor to determine the stride. A compression ratio is then determined according to the direction and the stride of adjustment.


