Colour enhancement processing of interior scene design images based on guided filtering

Aiming at the problems of traditional image colour enhancement methods, such as low average gradient, low standard deviation after enhancement, and low information entropy, an image colour enhancement processing method based on guided filtering was proposed for interior scene design. Firstly, a guided filtering algorithm is used to remove the noise in the interior scene design image, and a gradient domain guided filtering algorithm is used to extract the illumination component. Secondly, the correction weights are linearly stretched to different degrees to obtain adaptive gamma correction weights of different grey levels. Finally, colour compensation and enhancement of interior scene design images are achieved through gamma correction. The experimental results show that when the number of images is 6,000, the information entropy of the colour enhanced image in this method is 921 bits, the image standard deviation reaches 4.83, and the average gradient of the image is 23.8.

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Publication Details

Journal
International Journal of Reasoning-based Intelligent Systems
Published
2025-01-01
DOI
https://doi.org/10.1504/ijris.2025.147452
Primary Topic
Image Enhancement Techniques
Type
article
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article

Colour enhancement processing of interior scene design images based on guided filtering

Shashan Hou
International Journal of Reasoning-based Intelligent Systems
Image Enhancement Techniques
article

Colour enhancement processing of interior scene design images based on guided filtering

Shashan Hou
article en

Abstract

Aiming at the problems of traditional image colour enhancement methods, such as low average gradient, low standard deviation after enhancement, and low information entropy, an image colour enhancement processing method based on guided filtering was proposed for interior scene design. Firstly, a guided filtering algorithm is used to remove the noise in the interior scene design image, and a gradient domain guided filtering algorithm is used to extract the illumination component. Secondly, the correction weights are linearly stretched to different degrees to obtain adaptive gamma correction weights of different grey levels. Finally, colour compensation and enhancement of interior scene design images are achieved through gamma correction. The experimental results show that when the number of images is 6,000, the information entropy of the colour enhanced image in this method is 921 bits, the image standard deviation reaches 4.83, and the average gradient of the image is 23.8.

International Journal of Reasoning-based Intelligent SystemsVol. 17(3)
Sichuan University (CN)
Sustainable cities and communities
Openalex Percentile: Top 84%
Image Enhancement Techniques
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