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SYSTEM AND METHOD FOR STITCHING IMAGES USING NON-LINEAR OPTIMIZATION AND MULTI-CONSTRAINT COST FUNCTION MINIMIZATION

机译:非线性优化和多约束成本函数最小化的图像拼接系统和方法

摘要

The present disclosure provides a system and a method for stitching images using non-linear optimization and multi-constraint cost function minimization. Most of conventional homography based transformation approaches for image alignment, calculate transformations based on linear algorithms which ignore parameters such as lens distortion and unable to handle parallax for non-planar images resulting in improper image stitching with misalignments. The disclosed system and the method generates initial stitched image by estimating a global homography for each image using estimated pairwise homography matrix and feature point correspondences for each pair of images, based on a non-linear optimization. Local warping based image alignment is applied on the initial stitched image, using multi-constraint cost function minimization to mitigate aberrations caused by noises in the global homography estimation to generate the refined stitched image. The refined stitched image is accurate and free from misalignments and poor intensities.
机译:本公开提供一种用于使用非线性优化和多约束成本函数最小化来缝合图像的系统和方法。大多数传统的基于单应性的用于图像对齐的变换方法都是基于线性算法来计算变换的,该线性算法会忽略诸如镜头失真之类的参数,并且无法处理非平面图像的视差,从而导致不正确的图像拼接和错位。所公开的系统和方法基于非线性优化,通过使用估计的成对单应性矩阵和每对图像对的特征点对应关系来估计每个图像的全局单应性来生成初始缝合图像。使用多约束代价函数最小化来减轻全局单应性估计中由噪声引起的像差,从而将基于局部扭曲的图像对齐应用于初始拼接图像,以生成精炼的拼接图像。精致的缝合图像准确无误,并且没有不良强度。

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