关键词: 图像去噪, 卷积运算, 全变分（TV）图像去噪模型, 尺度不变特征变换（SIFT）特征匹配, 图像拼接, 图像融合

Abstract:

Panoramic image generation process is susceptible to noise. Aiming at this problem, an improved Total Variation（TV） image denoising model is proposed and applied to the Mosaic of panoramic images. Firstly, convolution operation is carried out on the functional function established in the process of image denoising, and the gray value of noise points is reduced by means of convolution operation. Then, the minimum value of Lagrange equation corresponding to the functional function is solved to achieve the effect of image denoising. Secondly, it uses the SIFT（Scale Invariable Feature Transformation） feature matching algorithm for denoising of image feature extraction and matching. Finally, the splicing image is weighted and fused to optimize the visual effect. The simulation results show that compared with the classical algorithm, this research can remove the noise in the image, reduce the interference in the process of panoramic image mosaic, and improve the visual effect.

Key words: image denoising, convolution operation, Total Variation（TV） image denoising model, Scale Invariable Feature Transfomation（SIFT） feature matching, image mosaic, image fusion