QR Code image super-resolution reconstruction method based on sparse representation

Abstract

The invention discloses a QR Code image super-resolution reconstruction method based on sparse representation, which solves the problem of super-resolution reconstruction of low-resolution QR Code two-dimensional code images. Using the edge gradient feature and texture feature of the QR Code two-dimensional code, the operator extracts the image feature to obtain the feature block; through the dictionary learning algorithm, obtain the learning dictionary of the low-resolution image block and the corresponding high-resolution image block; use sparse representation Theoretically, sparsely encode the input low-resolution image feature blocks, and combine the learning dictionary to obtain the high-resolution image blocks corresponding to the input low-resolution image blocks; apply global constraints to synthesize all high-resolution image blocks into the final high-resolution QR Code two-dimensional code image to achieve super-resolution reconstruction. The invention utilizes image characteristics to effectively reconstruct a high-resolution QR Code two-dimensional code image with clear edges and retains a large number of high-frequency details, and is suitable for super-resolution reconstruction of the QR Code two-dimensional code image.

Description

technical field [0001] The invention belongs to the technical field of digital image processing, and in particular relates to a QR Code image super-resolution reconstruction method based on sparse representation. Background technique [0002] QR Code two-dimensional code is widely used because of its information content and high density, and the performance of two-dimensional barcode recognition requires high-resolution QR Code two-dimensional code image to ensure. Most of the existing solutions are processed by increasing the resolution of the camera. However, this method has many limitations. For example, in the bank bill processing system, in order to simultaneously recognize the two-dimensional barcode, seal, amount and other elements on the bill, a 3800× 2400 or higher resolution, which is beyond the reach of most cameras. In addition, in some applications that require users to collect QR Code images and upload them to the server for recognition, due to the lack of suf...

AI Technical Summary

Problems solved by technology

The parameters of the degradation model of this method are difficult to estimate. In addition, the number of input images required increases with the increase of the resolution magnification factor. When the resolution magnification factor is too large, the increase in the number of input images cannot improve the reconstruction quality.

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