Image resolution is an important criterion to measure the quality of an image. High-resolution
images are a prerequisite for professionals to analyze problems and make accurate …

… Next, two features are integrated to get the saliency map with high robustness, and to
further refine our results, the known priors are incorporated on image organization, which can …

Aim at the problem that lower-order Markov random field (MRF) model is inefficient to capture
the rich prior knowledge of nature images which may bring out error image segmentation …

… the test sample’s sparse representation is constructed by all … M, image denoising via
sparse and redundant representations over learned dic tionaries. IEEE Transactions on Image …

… histogram is extracted via block, finally the test image can be classified as the existing class
via sparse representation. The experimental results based on AR face database show that …

… sparse representation in face recognition, this thesis proposes the non-negative sparse
representation … In addition, the Fisherface is combined to increase the recognition rate. There are …

… In order to identify nine species of rice forecasting pests from a large number of agricultural
insect images, a method based on multi-feature and sparse representation for pest image …