Overcomplete Research Articles

运动模糊退化图像的双字典稀疏复原

An image restoration method based on a dual dictionary was presented under the framework of sparse theory,and the choice of overcomplete dictionaries and the implementation of iteration methods were analyzed.Firstly,the degradation and the restoration models in the sparse theory were established,then the dictionary constructed by Haar coefficients was used to sparse the blurred image and shrink the image with Parallel Coordinate Decent(PCD) iteration algorithm to obtain the elementary deblurred image,in which the blur was removed efficiently,but the noise was weighted and added.For removing the weighted noise,the secondary dictionary from an image database was trained to shrink the deblurred image and get the final result.The results shows that the proposed method can restore the motion-blurred image efficiently,remove motion blur and noise and reserve the edge detail in some extents.Finally the two-level sparse optimization model was expanded and a new idea for the image restoration was presented under the sparse framework.

Two dictionaries matching pursuit for sparse decomposition of signals

Signal may be decomposed sparsely and power focally in an over-complete dictionary with matching pursuit (MP). In this paper, proposed is a modified MP method named two dictionaries MP (TDMP) to decompose signal more sparsely. In the iteration procedure of TDMP, the over-complete dictionary is classified into two separate dictionaries with the selected and unselected atoms, and in each iteration, the algorithm was designed to have more chances than the original MP to choose the atom in the selected atom dictionary as the optimal atom by the constraint of a simulate annealing threshold function, thus the algorithm avails for a more sparse decomposition. The decomposition results for a cosine-modulated exponential signal and an actual speech signal showed that the proposed TDMP could decompose signal more sparsely.

Modulus quantization for matching-pursuit video coding

Overcomplete signal decomposition using matching pursuits has been shown to be an efficient technique for coding motion-residual images in a hybrid video coder. Unlike orthogonal decomposition, mat...

Late Holocene record of community replacement preserved in time-averaged molluscan assemblages, Louisiana chenier plain

Late Holocene relict shorelines of the southwestern Louisiana chenier plain contain molluscan assemblages that vary greatly in taxonomic composition and bioclast preservation. Taxonomic composition varies with ridge age: older ridges are oyster rich, whereas younger ridges are dominated by infaunal bivalves. Taphonomic features can be separated into those caused by biostratinomic and those caused by pedogenic processes. Pedogenic alteration generally increases as ridge age increases, whereas biostratinomic alteration reflects the prevalence of reworked bioclasts in assemblages. These molluscan assemblages are extensively time averaged, causing temporal overcompleteness of depositional units (i.e., amount of time averaging for bioclasts within a unit is much greater than the time it took for that unit to form). Chenier-plain progradation over the last 3,000 years both caused and preserved the observed trend in community composition. This trend was caused by community replacement related to changing substrate stability and by changes in the source of reworked bioclasts, both of which operated in response to progradation. Net progradation also allowed this trend to be preserved because time averaging occurred episodically and shorelines were effectively separated into discrete generations. Although coastal deposits are not typically viewed as ideal sites for high-resolution paleoenvironmental studies, millennial-scale community trends can be detected in this setting.