Acoustic is the study of sound. Underwater acoustic plays an important role in understanding the undersea environment. Today, sonar systems become a common acoustic-based technology for underwater exploration. Signals reflected to the sonar systems can be used to construct an image in a raster scan structure. Such imaging sonars provide near-photographic images of underwater areas, even in zero visibility water. Image processing approaches for sonar systems are the main subject of this book. Underwater acoustic image processing consists of image acquisition, pre-processing, image feature extraction, image segmentation, and image classification. We developed new algoruthms and methods in all of the above categories. Due to highly textured appearance of sonar images, texture analysis methods become a common choice for acoustic images. This Book also discusses algorithms for textural feature extraction and classification applied to supervised segmentation of multi-textured images using wavelet and contourlet transforms. All the proposed schemes are compared with commonly used texture segmentation and classification methods on different image sets to show the fidelity of our methods.