Article: Research on image enhancement of smart home product layout scene based on virtual reality Journal: International Journal of Computer Applications in Technology (IJCAT) 2026 Vol.78 No.7 pp.1 - 9 Abstract: To elevate the quality of image enhancement for smart home product layout scenes and expedite processing times, a study focused on virtual reality-based enhancement of these scenes has been undertaken. Initially, a virtual reality framework is employed to create an indoor environment for smart homes, with the ISGSA algorithm model utilised to generate this environment. Subsequently, the attributes of each constituent element are amalgamated and fed into a generator to produce a novel indoor scene. Ultimately, a conditional generative adversarial network is devised to formulate a composite loss function, integrating channel colour loss, structural feature loss and smoothness loss. This loss function is instrumental in achieving image enhancement. Experimental findings reveal that the proposed method attains an average information entropy of 8.846, with an image enhancement processing duration of merely 3.9 s. Inderscience Publishers - linking academia, business and industry through research

Title: Research on image enhancement of smart home product layout scene based on virtual reality

Authors: Zhongmei Liu

Addresses: Shandong Huayu University of Technology, Dezhou, Zibo, Shandong, China

Abstract: To elevate the quality of image enhancement for smart home product layout scenes and expedite processing times, a study focused on virtual reality-based enhancement of these scenes has been undertaken. Initially, a virtual reality framework is employed to create an indoor environment for smart homes, with the ISGSA algorithm model utilised to generate this environment. Subsequently, the attributes of each constituent element are amalgamated and fed into a generator to produce a novel indoor scene. Ultimately, a conditional generative adversarial network is devised to formulate a composite loss function, integrating channel colour loss, structural feature loss and smoothness loss. This loss function is instrumental in achieving image enhancement. Experimental findings reveal that the proposed method attains an average information entropy of 8.846, with an image enhancement processing duration of merely 3.9 s.

Keywords: virtual reality; smart home products; layout scene; image enhancement; ISGSA algorithm; attention learning module; channel colour loss.

DOI: 10.1504/IJCAT.2026.153763

International Journal of Computer Applications in Technology, 2026 Vol.78 No.7, pp.1 - 9

Received: 09 Apr 2025
Accepted: 08 Aug 2025
Published online: 26 May 2026 *

Title: Research on image enhancement of smart home product layout scene based on virtual reality

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