39 results about "Entropy rate" patented technology

A method, system and computer program product are provided for progressively encoding a digitized color image with M distinct colors allocated to a set of pixels using a data processing system, the digitized color image being provided by assigning each of the M distinct colors to at least one pixel in the set of pixels. This involves: (a) initializing a tree structure by providing at least one starting leaf node comprising a subset of pixels from the set of pixels; (b) determining at least one representative color for each starting leaf node; and (c) growing the tree structure by (i) selecting a leaf node n to become a non-leaf node n linked to two new leaf nodes based on an associated achievable cost, wherein the associated achievable cost is determined by 1) determining an associated change in distortion resulting from turning the leaf node into the non-leaf node linked to the two new leaf nodes; 2) determining an associated increase in entropy rate resulting from turning the leaf node into the non-leaf node linked to the two new leaf nodes; and, 3) determining the associated achievable cost based on the associated change in distortion and the associated increase in entropy rate; (ii) creating the two new leaf nodes by allocating each pixel in n to one of the two new leaf nodes; (iii) determining a representative color for each of the two new leaf nodes; and (iv) encoding the index information associated with the leaf node n, the representative colors of the two new leaf nodes, and information regarding each pixel in n.

An image is segmented into superpixels by constructing a graph with vertices connected by edges, wherein each vertex corresponds to a pixel in the image, and each edge is associated with a weight indicating a similarity of the corresponding pixels, A subset of edges in the graph are selected to segment the graph into subgraphs, wherein the selecting maximizes an objective function based on an entropy rate and a balancing term. The edges with maximum gains are added to the graph until a number of subgraphs is equal to some threshold.

The invention discloses an automatic random-walk CT lung parenchyma image segmentation method based on prior information. The method comprises the following steps that an original CT image is input, and binary discrete wavelet transformation is carried out on the input CT image to obtain an image M; a chest area is extracted from the image M in an entropy based superpixel method, and then processed to obtain an image T; the amount and position of seed points of the image T are obtained by utilizing the prior information guided by anatomy knowledge, and random-walk segmentation is carried out on the obtained seed points to obtain an initial parenchyma contour of the lung; and local mis-segmented areas of the initial parenchyma contour of the lung are repaired in a curvature rectification algorithm. Thus, the method of the invention can be used to solve the technical problem that in the present random-walk technology, the segmented lung parenchyma image is greatly influenced by the amount and positions of the seed points when the seed points are selected by manual interaction.

The invention relates to a large-format remote sensing image building extraction method for mixed scenes. It includes the following steps: step 1, preprocessing the remote sensing image; step 2, performing superpixel segmentation based on entropy rate; step 3, extracting three features of shadow, homogeneity and strong edge; step 4, generating shadow layer, Homogeneity layer and strong edge layer; step 5, extract buildings on different layers; step 6, building overlay. The beneficial effect of the present invention is that more features and deeper semantic information can be extracted, which can be adapted to extract buildings in a larger geographical area and be used to realize related services such as update of urban basic geographic databases.

The invention belongs to the technical fields of information security and true random number generators, and specifically relates to a method for testing the maximum entropy rate of true random number generators. The method for testing the maximum entropy rate of a true random number generator disclosed by the invention includes four steps: parameter selection, data collection, block calculation, and analysis and fitting. The present invention utilizes the characteristic that the average entropy rate calculated after the random data flow is divided into blocks is saturated with the decrease of the data block length and the increase of the data rate, and performs linear fitting on the relationship curve between the saturated entropy rate and the data block length, and simulates The corresponding function value of the straight line when the data block length is 1 is the maximum entropy rate. The invention can effectively solve the problem that the maximum entropy rate cannot be uniquely determined in the test of the true random number generator.

The invention relates to a method for testing and diagnosing the cause of performance attenuation of a lithium-ion battery, comprising measuring the ohmic impedance and relaxation impedance of a battery to be tested and a reference battery during charging and discharging under a certain state of charge; The temperature entropy coefficient of the battery to be tested and the reference battery; calculate the ohmic impedance growth rate and relaxation impedance growth rate and the absolute value of the temperature entropy coefficient growth rate of the battery relative to the reference battery in the charging and discharging process; Comparing the ohmic impedance growth rate and relaxation impedance growth rate and the absolute value of the temperature entropy coefficient growth rate of the battery under test relative to the reference battery, the cause of battery performance attenuation can be judged. The invention avoids the influence of other factors introduced into the assembly process after the battery is disassembled, and greatly improves the accuracy of testing and judgment; and the operation process and method are simple, which is convenient for testing multiple battery samples and establishing a corresponding database, which can reduce battery performance attenuation. Analysis provides reliable reference data.

The invention discloses a visual attention computing method and a system based on bit entropy rate. The method includes that: a sparse codebook is learned to obtain a sparse codebook primary function; the sparse codebook primary function is adopted to filter the image or video data and obtain a plurality of sub-band feature graphs; a corresponding fully-connected graph is established for each sub-band feature graph; the information transfer method of each fully-connected graph adopts the random walk method, during the random walk process, the significance measurement is performed according tothe bit entropy rate to accordingly obtain a bit entropy rate graph corresponding to each sub-band feature graph; the bit entropy rate graphs are added together to obtain the significance graph of the image or video data. As indicated in large amount of experiments, and compared with other methods in prior art, the analysis result of image significance analysis or video significance analysis obtained through the invention is more accurate and is supported by the basis of physiology and psychology.