The process of seamlessly combining many Virtual reality (VR) scenes to create a continuous and engaging VR experience is known as VR scene stitching. It comprises stitching together several scenes or locations to provide smooth transitions between them without any noticeable seams or interruptions. Each VR scene is carefully designed and created, focusing on certain areas, objects, or events within the virtual environment. To enhance the expertise based on the already employed animation VRSSM (VR scene stitching modeling), more research is conducted on the animation VRSSM in conjunction with Genetic Algorithms (GA). The approach uses a wavelet transform (WT) to recover the scene's low-and high-frequency components for use in animation. Splicing criteria for the high-frequency coefficients are determined by comparing and filtering the convolution outcomes from 2 GA pattern operators. The GA sharpness assessment function and the 8 neighborhood local variance are used to determine the splice procedure for the low frequency coefficients; to produce the mosaic modeling of the stitching scene; the inverse WT is utilized. The subjective and objective assessment approaches are used together to examine the experimental outcomes. The data demonstrate that the GA achieves a higher quality splice (0.38) than the traditional splicing modeling. Rich edge information and great scene clarity are benefits of animation scene splicing modeling. The method suggested in this study outperforms the standard algorithm in terms of both qualitative and quantitative evaluation, and its implementation yields a potent synergistic impact on VR scene stitching.Povzetek: Raziskava izboljšuje združevanje VR scen z uporabo genetskih algoritmov in valčne transformacije, kar omogoča kakovostnejše in bolj jasne prehode med scenami.