Image splicing method for reserving image correlation information

Abstract

The invention discloses an image splicing method for reserving image correlation information. The method comprises the following steps: step 1, performing correlation analysis, i.e., acquiring images to be spliced to obtain an image set, enabling each image to obtain a type label, then embedding the correlation information of the images into initial display panel distribution by use of a t distribution random field embedding method e-SNE method, and obtaining t-SNE distribution results; step 2, initializing display panel sub areas; step 3, performing display panel sub area division, i.e., through combination with a sub area optimization and wrong position correction method, determining an orientation angle theta, an arrangement position and a zooming scale of each image, and ensuring that the correlation information of the images is not lost; and step 4, performing seamless hybrid rendering, i.e., based on a probability hybrid model, performing the seamless hybrid rendering on a boundary area between the display panel sub areas so as to complete image concentration and image cutting splicing.

Description

technical field [0001] The invention belongs to the fields of computer image, multimedia information technology and the like, and in particular relates to a picture splicing method for preserving picture correlation information. Background technique [0002] With the increasing popularity of hand-held camera devices, it is more convenient for people to take pictures, and the pictures they get are more abundant, and then the demand for automatic management technology of picture collections is more prominent. As an important image collection summarization and presentation technique, image collage has been receiving more and more attention in recent years. The main purpose of a photo collage is to provide a compact, rich and aesthetically pleasing summary of a photo collection. Since manual production of such a collage summary map requires some professional image editing skills and is time-consuming, automated collage summary map generation technology has become a research hot...

AI Technical Summary

Problems solved by technology

First, the optimal state parameters of each picture are often tightly coupled with the states of several other pictures, causing the update of a certain picture state to affect other pictures globally or locally, resulting in poor scalability of the collage

Second, the image collection used for stitching often contains a lot of semantic information. Previous methods ignore this important information and just stitch the images together randomly.

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