Simulation of Modern Garden Landscape Image Optimization and Spatial Feature Distribution Based on 3D Modeling Technology

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Xiaofei Lu, Shouwang Li


The simulation of modern garden landscape image optimization and spatial feature distribution represents a promising approach to enhancing the quality and functionality of outdoor spaces using 3D modelling technology. This study explores the integration of image optimization techniques and spatial feature distribution analysis within a comprehensive simulation framework to optimize the design of garden landscapes. Through a series of experiments and analyses, the effectiveness of different combinations of image optimization parameters and spatial feature distribution parameters is evaluated. Results demonstrate that specific configurations yield significant improvements in both visual quality, as measured by Peak Signal-to-Noise Ratio (PSNR), and spatial coherence, as assessed by Circulation Efficiency metrics. Experiment 2 emerged as the most successful configuration, achieving high image quality and superior spatial coherence. These findings highlight the importance of holistic design approaches in landscape architecture, where considerations of both aesthetic appeal and functional usability are paramount. Moving forward, future research directions could focus on refining simulation methodologies, exploring additional design factors, and validating simulated landscapes in real-world settings. Overall, this study contributes to advancing the field of landscape architecture by demonstrating the potential of 3D modelling technology to create immersive and sustainable garden landscapes that inspire and delight users.

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