Single image super resolution based on sparse representation via structurally directional dictionaries

Turkic-Mongolian relations and the borrowings between these two language families have always been an interesting field of study for lexicographers. Even more interesting is the

Batı Çin bölgesinde konuşulan ve uzaktan ilişkili olan birkaç Türk dili hariç Türk dilleri birbirleriyle çok yakından bağlantılıdır ve bunların Orta Çağ'da Orta

In this thesis a dictionary learning algorithm based on coupled K-SVD [10] in wavelet domain is proposed and it is applied to the problem of Single Image Super- Resolution

dictionary learning algorithm based on coupled K-SVD in wavelet domain is proposed and it is applied to the problem of Single Image Super-Resolution (SISR).. Now let

In this thesis we proposed a semi-coupled dictionary learning algorithm for single image super-resolution, which contain number of dictionaries with a mapping

The training phase is finished by learning high and low resolution dictionaries.. This phase has tested for the images which they have down sampled and blurred by the same factors

Given the simplicity of bicubic interpolation and the fact that a large percentage of patches lies in the clusters of insignificant high frequency components, one can

6.2.1 Residual component-based dictionary learning and sparse representation The above observations suggest a strategy for learning multiple structured dictionaries based on