Background-Removed Image Compression for Subject Extraction
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Solution Overview
Problem
Existing image processing methods that transmit images with maintained quality over networks increase communication load and deteriorate the quality of the extracted subject due to compression.
Innovation Solution
Generate a background removed image by removing the background region from the original image, compress this image, transmit it over the network, decode and synthesize it with the background image to extract the subject, thereby maintaining the quality of the subject region.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If an image including a subject is transmitted with quality maintained via a network, then the image quality is preserved, but the communication load increases
Solution Approach 1:
The image is segmented into subject region and background region. Only the subject region is transmitted with high quality, while the background region is transmitted with reduced quality or omitted entirely. This segmentation allows preserving image quality for the important subject portion while reducing overall data transmission volume.
Solution Approach 2:
The subject region is extracted from the full image for separate transmission. By taking out only the necessary subject portion and transmitting it with maintained quality, the communication load is reduced compared to transmitting the entire high-resolution image, while still achieving the goal of preserving subject image quality.
2Quantity of substance
If an image is compressed to reduce communication load, then the communication load decreases, but the extracted image quality deteriorates
Solution Approach 1:
The image is divided into subject and background regions with different compression strategies. The subject region is compressed with lower compression ratio to maintain quality, while the background region uses higher compression ratio. This selective segmentation approach reduces overall communication load while preserving subject image quality.
Solution Approach 2:
Different quality levels are applied to different regions of the image. The subject region maintains high quality with minimal compression, while the background region accepts higher compression. This local quality differentiation allows reducing total data size while ensuring the important subject portion remains high quality.
3Quantity of substance
If the background region is removed from the image before transmission, then the data amount is reduced, but the processing complexity increases
Solution Approach 1:
The background removal and region segmentation are performed in advance at the transmission end before the image is sent over the network. By performing this preprocessing action preliminarily, the data amount to be transmitted is reduced, and the receiving end can focus on decoding and reconstruction without the complexity of background removal.
Data Source
AI summary
An image processing method for extracting a subject from an image including the subject using a background image includes: generating a background removed image obtained by removing a background region not including the subject in the image from the image; compressing the background removed image; transmitting the background removed image compressed via a network; receiving the background removed image compressed via the network; decoding the background removed image compressed and received; generating a restored image by synthesizing the background removed image decoded and the background image; and comparing the restored image with the background image to extract the subject.