Multiple pixel methods

Lecture Digital image processing - Chapter 3: Image enhancement in the spatial domain provide students with content about: single pixel methods; multiple pixel methods; point processing; gray level transformations; arithmetic/logic operations;... Please refer to the detailed lecture content!

98p diepkhinhchau 18-09-2023 9 4   Download

A Gaussian mixture model (GMM)-based classification technique is employed for a quantitative global assessment of brain tissue changes by using pixel intensities and contrast generated by b-values in diffusion tensor imaging (DTI). A hemisphere approach is also proposed. A GMM identifies the variability in the main brain tissues at a macroscopic scale rather than searching for tumours or affected areas. The asymmetries of the mixture distributions between the hemispheres could be used as a sensitive, faster tool for early diagnosis.

9p trinhthamhodang1 14-11-2019 11 0   Download

This paper presents the improved multiple-source Dijkstra algorithm as an efficient solution to the multiple objects, interactive image segmentation problem, which can be applied for precomputing process in many tasks of image processing. Given an input image, we can build a sparse undirected graph of pixels and pick some pixels with predefined labels as sources.

11p visumika2711 17-07-2019 15 0   Download

4.2.3 MTMF MTMF combines the best parts of the Linear Spectral Mixing model and the statistical Matched Filter model while avoiding the drawbacks of each parent method (Boardman, 1998). It is a useful Matched Filter method without knowing all the possible endmembers in a landscape especially in case of subtle, sub-pixel occurrences. Firstly, pixel spectra and endmember spectra require a minimum noise fraction (MNF) (Green et al., 1988, Boardman, 1993) transformation. MNF reduces and separates an image into its most dimensional and non-noisy components.

464p lulanphuong 22-03-2012 181 44   Download