Image Processing Apparatus for Bit Rate Optimization
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Solution Overview
Problem
Existing image processing systems for surveillance cameras face challenges in efficiently managing bit rates and image quality, particularly in real-time surveillance environments where events such as object movement or scene changes can lead to increased bit rates and resource inefficiencies.
Innovation Solution
An image processing apparatus and method that includes an image processor to enhance edges, remove noise, and reduce high frequencies, and an encoder to adjust quantization parameters and frame rates based on detected events, thereby optimizing bit rates and improving compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If image processing is performed with high compression rates to reduce transmission bit rate, then transmission efficiency is improved, but image quality deteriorates
Solution Approach 1:
The patent applies preliminary action by performing edge enhancement and noise removal on the image before compression. The image processor enhances edges and removes noise in advance, so that when compression is applied, the important image features are already optimized and better preserved despite the compression artifacts
Solution Approach 2:
The patent changes parameters by dynamically adjusting the quantization parameter (QP) based on detected events. When events such as motion or scene changes are detected, the system modifies compression parameters to maintain image quality in critical regions while still achieving overall bit rate reduction
2Measurement precision
If event detection is implemented to improve surveillance accuracy, then detection precision is improved, but processing complexity increases
Solution Approach 1:
The patent applies local quality by performing event detection and processing at different levels for different regions of the image. The system detects events such as motion and scene changes, then applies different processing strategies to affected regions versus normal regions, reducing overall processing complexity while maintaining detection accuracy
Solution Approach 2:
The patent introduces an intermediary event detection mechanism that acts as a mediator between raw image input and full processing. The event detector identifies significant changes and triggers appropriate processing only when needed, reducing unnecessary processing complexity while maintaining detection precision
3Loss of energy
If quantization parameter is increased to reduce bit rate, then transmission efficiency is improved, but image quality deteriorates
Solution Approach 1:
The patent dynamically changes the quantization parameter based on event detection and image content analysis. Instead of using a fixed high QP value, the system adjusts QP adaptively - using higher values in less important regions and lower values in regions containing important features or events, thus achieving bit rate reduction while preserving image quality where needed
Solution Approach 2:
The patent applies different quantization parameters to different regions of the image. Important regions such as areas with detected events or high-frequency content receive lower quantization (better quality), while less important regions receive higher quantization (lower quality), achieving overall bit rate reduction without uniform quality loss
Data Source
AI summary
An image processing apparatus includes an image processor and an encoder. The image processor enhances an edge of an input image, removes noise from the input image, synthesizes the edge-enhanced image and the noise-removed image, and removes a high frequency from the synthesized image. The encoder pre-encodes a downsized synthesized image, obtains a pre-bit rate of the pre-encoded image, sets a quantization parameter value based on a reference bit rate and the pre-bit rate, and compresses the high-frequency removed image based on the quantization parameter value.