![]() In the context of the paper low entropy (H(s_m) means low disorder, low variance within the component m. So what does this mean? In image processing entropy might be used to classify textures, a certain texture might have a certain entropy as certain patterns repeat themselves in approximately certain ways. ![]() The probability density p_n is calculated using the gray level histogram, that is the reason why the sum runs from 1 to 256. Here is the probability that outcome s_m happens. H(s_m) is the entropy of the random variable s_m. As the level of disorder rises, the entropy rises and events become less predictable.īack to the definition of entropy in the paper: Entropy can serve as a measure of 'disorder'. One way to view entropy is to relate it to the amount of uncertainty about an event associated with a given probability distribution. They are talking about Shannon's entropy. The target component is a tumor and the paper reads: "the tumor related component with "almost" constant values is expected to have the lowest value of entropy."īut what does low entropy mean in this context? What does each bin represent? What does a vector with low entropy look like? But I'm failing to understand what entropy is in this case.Īnd they say that '' are probabilities associated with the bins of the histogram of '' ![]() In the paper I'm reading, the authors wish to select a component m for which matches certain smoothness and entropy criteria. T is the total number of pixels in the image, is the value of the source component (/signal/object) i at pixel j ![]() The output of the algorithm is a matrix, which represents a segmentation of an image into M components. I'm reading an image segmentation paper in which the problem is approached using the paradigm "signal separation", the idea that a signal (in this case, an image) is composed of several signals (objects in the image) as well as noise, and the task is to separate out the signals (segment the image). ![]()
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |