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A sub-pixel location method for interest points by means of the Harris interest strength

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The sub-pixel location of interest points is one of the most important tasks in refined image-based 3D reconstruction in digital photogrammetry. The interest point detectors based on the Harris principles are generally used for stereoscopic image matching and subsequent 3D reconstruction. However, the locations of the interest points detected in this way can only be obtained to 1 pixel accuracy. The Harris detector has the following characteristics: (1) the Harris interest strength, which denotes the distinctiveness of an interest point, is a grey scale descriptor which computes the gradient at each sample point in a region around the point, and (2) the Harris interest strengths of the pixels in a template window centred on the interest point exhibit an approximately paraboloid distribution. This paper proposes a precise location method to improve the precision of the interest points on the basis of these characteristics of the Harris interest strength. Firstly, a least squares fit of a paraboloid function to the image grey scale surface using the Harris interest strength is designed in a template window and a Gaussian-distance algorithm is employed to determine the weight. Then, the precise coordinates of this interest point are obtained by calculating the extremities of the fitting surface. The location accuracy of this method is studied both from the theoretical and the practical point of view. Experimental analysis is illustrated with synthetic images as well as actual images, which yielded a location accuracy of 0ยท15 pixels. Furthermore, experimental results also indicate that this method has the desired anti-image-noise and efficiency characteristics.
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Keywords: Gaussian-distance weight determination; Harris interest strength; least squares fitting; sub-pixel location

Document Type: Research Article

Affiliations: 1: ( ), Email: [email protected] 2: ( )State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, China, Email: [email protected]

Publication date: 2007-12-01

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