Image Processing Using Distance-Based Area Segmentation
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Solution Overview
Problem
Existing image processing technologies face challenges in compressing image data without compromising image quality, especially when transferring high-resolution or high-frame-rate moving images, often resulting in frame drops due to bandwidth limitations.
Innovation Solution
An image processing apparatus and method that utilize distance information from a distance measurement sensor to divide an image into areas with differing qualities, such as resolution or frame rate, allowing for targeted compression by generating multiple images with varying qualities based on attention and non-attention areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If image resolution or frame rate is increased to improve image quality, then image quality is improved, but data amount increases causing frame drops due to bandwidth limitations
Solution Approach 1:
The image is divided into multiple regions based on distance information from the depth sensor. Each region is independently processed with different compression rates, allowing important regions (near subjects) to maintain high quality while less important regions (background) use higher compression, thus reducing overall data amount while preserving image quality.
Solution Approach 2:
Different compression rates are applied to different regions of the image based on their importance. Regions containing subjects at various distances are assigned different quality levels, with closer subjects receiving higher quality preservation and distant background receiving lower quality, optimizing the balance between image quality and data transmission efficiency.
2Quantity of substance
If uniform compression is applied to the entire image to reduce data amount, then data amount is reduced, but image quality deteriorates in important regions
Solution Approach 1:
The image is segmented into multiple regions based on distance information, with each region assigned a different compression rate. This allows the system to apply aggressive compression to background regions while maintaining high compression rates for regions containing subjects, thus reducing overall data amount without sacrificing image quality in important areas.
Solution Approach 2:
Different compression rates are locally applied to different image regions based on their semantic importance derived from depth information. Important regions (subjects) maintain high quality with lower compression, while less important regions (background) accept higher compression, achieving optimal balance between data reduction and quality preservation.
3Productivity
If distance information is used to divide image areas for differential processing, then image data compression efficiency is improved, but processing complexity increases
Solution Approach 1:
Depth information from a distance measurement sensor serves as an intermediary to guide the image processing. This depth map provides ready-made spatial segmentation information that simplifies the division of image regions, avoiding the need for complex computer vision algorithms while enabling efficient differential compression based on object distance.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables efficient compression of image data using distance information, reducing the overall data amount transmitted while maintaining image quality, and allows for real-time transmission of compressed images without requiring inter-frame correlations.
Implementation Method 1
Some image pickup apparatuses such as a digital still camera and a digital video camera include a distance measurement sensor that measures a distance to a subject using, for example, a ToF system
Data Source
AI summary
The present technology relates to an image processing apparatus, an image processing method, and an image pickup apparatus that enable image data to be compressed using distance information.An image processing apparatus includes an image processing unit that divides an image area of a predetermined image into at least two areas on the basis of distance information obtained by a distance measurement sensor, and executes image processing on at least one of the two areas of the image such that image qualities of the two areas differ. The present technology is applicable to, for example, an image pickup apparatus and the like.