In recent years

the study of image super-resolution reconstruction technology has been paid much attention to

because it can improve image recognition accuracy and recognition ability. One of the difficult problems is how to ensure the reconstruction quality of image edge texture area. In this paper

a single image super-resolution reconstruction approach based on wavelet domain is proposed. Firstly

the non-subsampled wavelet transform (NSWT) is applied to the input image

according to the multi-directionality of wavelet transform

three kinds of multi-angle templates are proposed

and each subband contour is estimated by total variation model (TV model) to determine its optimal direction. Then

the multi-angle templates and bicubic B-spline interpolation are used to interpolate the subbands. Finally

the non-subsampled wavelet inverse transform is implemented. This approach makes edge information and texture information of the reconstructed images more precise

and overcomes some deficiencies such as edge blurring

edge serration

as well as distortion of texture region

caused by traditional interpolation reconstruction approaches

such as bilinear interpolation and bicubic interpolation

etc. The quality of reconstructed image is improved. This approach can be used in image monitoring

remote sensing image analysis

medical image processing

and so on. A large number of simulation experiments verify the effectiveness of the proposed approach.