Image Stitching Method for Surround View Image without Seamline

Jin-Hyuk Choi, Heunseung Lim, Sang-Suk Yun, Minwoo Shin, J. Paik
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Abstract

The surround view system delivers the surrounding environment to the driver in a top-down manner so that the driver can recognize blind spots. In this system, image stitching is combining camera images facing different directions into a single image. As an easy-to-access method, there is a method of warping through homography by extracting and matching the features of the images to be stitched. However, this method has a limitation in that stitching is not performed properly if the geometric distortion is severe. In order to solve this problem, a method of estimating a seam and stitching images is being studied in many existing methods, and a representative method is a method using a distance matrix using the difference of gradient components. However, this method has a problem of falling into the local minima and causing a loop phenomenon. To solve this problem, we propose a seamline estimation method using ℓ0-norm based gradient priors. The optimal seam can be found by obtaining the energy matrix through ℓ0-gradient priors and estimating the distance matrix through this. In this method, improved seam estimation is possible because the shortest distance is calculated as the point where the rate of change between the two images is minimized.
无缝线的环绕视图图像拼接方法
环视系统以自上而下的方式向驾驶员提供周围环境,以便驾驶员识别盲点。在该系统中,图像拼接是将面向不同方向的摄像机图像组合成一幅图像。作为一种易于获取的方法,有一种通过提取和匹配待缝合图像的特征进行单应性翘曲的方法。然而,该方法的局限性在于,如果几何畸变严重,则无法正确地进行拼接。为了解决这一问题,在现有的许多方法中,人们正在研究一种估计缝线和拼接图像的方法,其中比较有代表性的方法是利用梯度分量差来建立距离矩阵的方法。然而,这种方法有陷入局部极小值并引起循环现象的问题。为了解决这一问题,我们提出了一种基于0范数梯度先验的缝线估计方法。通过0梯度先验获得能量矩阵,并以此估计距离矩阵,从而找到最优缝。在这种方法中,改进的接缝估计是可能的,因为最短距离被计算为两个图像之间变化率最小的点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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