By Ludwik Kurz

ISBN-10: 0511530161

ISBN-13: 9780511530166

ISBN-10: 0521031966

ISBN-13: 9780521031967

ISBN-10: 0521581826

ISBN-13: 9780521581820

A key challenge in useful picture processing is the detection of particular positive factors in a loud photograph. research of variance (ANOVA) concepts could be very powerful in such occasions, and this ebook offers an in depth account of using ANOVA in statistical snapshot processing. The e-book starts by way of describing the statistical illustration of pictures within the numerous ANOVA types. The authors current a couple of computationally effective algorithms and methods to house such difficulties as line, part, and item detection, in addition to photograph recovery and enhancement. by means of describing the elemental ideas of those suggestions, and exhibiting their use in particular occasions, the publication will facilitate the layout of latest algorithms for specific purposes. it is going to be of significant curiosity to graduate scholars and engineers within the box of photograph processing and trend popularity.

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**Extra info for Analysis of Variance in Statistical Image Processing**

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T\ j = 1, 2, . . , b. 80) where /x is the general mean, a,- is the treatment effect subject to the condition Yfi=i ai — °> a n d Pj i s t h e block effects subject to X)y=i A/ = °The hypotheses of interest are the following Ha : all at = 0, that is, no treatments effects are present. Hi, : all Pj = 0, that is, no block effects are present. 81) Consider the following parameters for the BIB design: • b: number of blocks in the design • t: number of treatments in the design • k: number of treatments in a block.

2. A typical 5 x 5 layout is shown in Fig. 4. Note that the design is the nonrandomized version of the Graeco-Latin square, that is, the arrangement is such that every treatment is coupled exactly once with every treatment. The treatments in Fig. 4 Multidirectional line detectors 45 are the rows, columns, and Greek and Latin letters. The model in this case allows the simultaneous detection in any of the four distinct directions. Recalling Eq. 17) where of, yS, r, and 5 are such that a = {a\, oii, • • •» ^m}9 ^ = {)8i, ^2» • • • ?

F5p, then • A pairwise function among the effects is of the form ft —fijwhere / = 1, 2 , . . , p; j = 1 , . . , p and i ^ j . 30 Statistical linear models • A contrast function among the effects is of the form Zw=i cjPj where • A linear combination of the effects is of the form Yfj=\ cjPj • Notice that the pairwise as well as the contrast functions are special cases of the linear combination functions. 7 Multiple comparisons techniques The techniques outlined in this section are those that are the most relevant from the practical point of view.