Please note that signal/image processing and classification theory are quite different affairs, and that recommending books is difficult because people usually don’t prefer the same style of presentation and explanation.
Mainly because it is directly related to ImageJ and because it it easy to read I’d like to point you to:
Burger W. and Burge M.J. (2016, 2nd ed.)
Digital image processing: An algorithmic introduction using Java.
Springer, Berlin, New York, (811 pages).
ISBN: 978-1-4471-6683-2 (Hardcover), 978-1-4471-6684-9 (e-Book)
… and please have a look at it here:
Classifiers and classification
This topic is much more difficult to treat, especially because the field has considerably frayed during the past about 15 years. Not that there are really much new developments of theoretical approaches but the terminology has changed and there was a great deal of development concerning practical aspects, i.e. implementations adapted to modern computer technology.
That having been said, I’d like to recommend a book about the theoretical basics that includes a unification of statistical and network approaches. The author was a leading person in pattern recognition and his group built the then most successful classifiers for character recognition.
Schürmann J. (1996)
Pattern classification. A unified view of statistical and neural approaches.
Wiley, New York/NY (392 pages).
ISBN 978-0-471-13534-0 (Hardcover)
I don’t know about a good book dealing with more “applied” aspects, but, for obvious reasons, I’d try searching for “WEKA”.