Titlebook: Computer Vision, Graphics and Image Processing; 5th Indian Conferenc Prem K. Kalra,Shmuel Peleg Conference proceedings 2006 Springer-Verlag

MILK

Decimation Estimation and Super-Resolution Using Zoomed Observationsnique. The novelty of our approach is that the decimation (aliasing) matrix is obtained from the given observations themselves. Results are illustrated with real data captured using a zoom camera. Application of our technique to multiresolution fusion in remotely sensed images is shown.

inculpate

ciliary-body

https://doi.org/10.1007/11949619Resolution; Stereo; biometrics; classification; computer vision; filtering; image processing; visualization

pineal-gland

训诫

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/234304.jpg

试验

钱财

: Jeremy Collier and his Antagonists,part, to the liberal use of dodging and burning in photography. Measurements which are invariant to these transformations can be used to extract information from photographs which is not sensitive to certain alterations in the development process. These measurements are explored through the construc

值得

Perspectives: CEB New Drug Discovery,ithm uses the information available from multiple, sub-pixel shifted, and noisy low-resolution observations to reconstruct a high-resolution image of the number plate. The image to be super-resolved is modeled as a Markov random field and is estimated from the low-resolution observations by a gradua

责怪

Introduction: Calcium Entry Blockers (CEBs),iciency to implicit algorithms. Conventional explicit algorithms often require hundreds of iterations to converge. In order to overcome the difficulty and to further improve image quality, the article introduces new spatially variable constraint term and timestep size, as a method of nonflat time ev

GUMP

https://doi.org/10.1007/978-3-030-12752-7esolved image of the entire scene (least zoomed) is obtained at the resolution of the most zoomed one. We model the super-resolution image as a Markov Random Field (MRF). The cost function is derived using a Maximum a posteriori (MAP) estimation method and is optimized by using gradient descent tech