Fractal Image Compression by Yuval Fisher

By Yuval Fisher

This publication offers the speculation and alertness of latest equipment of photograph compression in accordance with self-transformations of a picture. those tools bring about a illustration of a picture as a fractal, an item with aspect in any respect scales. Very functional and entirely updated, this booklet will function an invaluable reference for these operating in photograph processing and encoding and as an outstanding advent for these unexpected with fractals. The e-book starts with an trouble-free advent to the idea that of fractal photo compression and incorporates a rigorous description of the entire appropriate mathemtics of the themes.

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2 Deep Belief Network A DBN is a probabilistic, generative model made up of multiple layers of hidden units [30]. It can be regarded as a composition of simple learning modules which make up each layer. A DBN can be used for generatively pretraining a DNN by using the learned weights from the DBN as the initial weights of the DNN. Backpropagation or other discriminative algorithms can then be employed to fine-tune these weights. This is particularly useful in situations with the limited number of training data since the initial weights are influential on the performance of the final model.

To detect scale-space extrema, the image is first convolved with Gaussian blur kernels at different scales. The convolved images are grouped by octave (an octave corresponds to doubling the value of σ ), and the value of ki is selected so that we obtain a fixed number 44 3 Image Features and Feature Processing Fig. 5 Maxima and minima of the DoG images are detected by comparing a pixel (marked with X) to its 26 neighbors in 3 × 3 regions at the current and adjacent scales (marked with circles) Fig.

Lecture Notes in Computer Science, vol 2756. Springer, pp 149–156 78. Ong E, Lin W, Lu Z, Yao S, Yang X, Jiang L (2003) No reference JPEG-2000 image quality metric. In: Proceedings of IEEE international conference multimedia and expo (ICME), pp 545–548 79. Faugeras OD (1979) Digital color image processing within the framework of a human visual model. IEEE Trans Acoust Speech Signal Process 27:380–393 80. Mannos J, Sakrison D (1974) The effects of a visual fidelity criterion of the encoding of images.

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