JOURNAL ARTICLE
Color Design of Home Based on Computer Cloud Image Processing Technology.
Published In: International Journal of High Speed Electronics & Systems, 2025, v. 34, n. 4. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Liu, Xia; Wang, Yin 3 of 3
Abstract
Different materials used in a home (such as wood, metal and glass.) will affect the presentation of color, which may cause color deviation or change. At the same time, the color of some household products will change or fade after a period of use, which may lead to the original design color effect no longer meeting the expectations. Therefore, in order to ensure the accuracy of color matching and meet the needs of color matching in home design, a color design method in home field based on computer cloud image processing technology is proposed. First, the method collects and preprocesses the images in the home field, and stores the collected images on the cloud platform. Then, the improved non-mean filtering algorithm is used to denoise the home domain image downloaded from the cloud platform. Then, white balance preprocessing is performed on the home image with color deviation by using the color deviation detection method of color distortion factor to ensure color accuracy. Finally, the contrast enhanced home image is converted to HSV color space, and saturation compensation is carried out in the channel to complete the color design in the home field. The experimental results show that this method has lower packet loss rate, better denoising effect and color balance in the cloud transmission of home image. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of High Speed Electronics & Systems. 2025/12, Vol. 34, Issue 4, p1
- Document Type:Article
- Subject Area:Engineering
- Publication Date:2025
- ISSN:0129-1564
- DOI:10.1142/S0129156425402773
- Accession Number:186254802
- Copyright Statement:Copyright of International Journal of High Speed Electronics & Systems is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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