Modern sidescan sonars produce echographs that look rather like aerial photographs of the seafloor, with a few important differences. Not least is their obvious sonar speckle---random pixel-to-pixel variations of the image intensity across flat surfaces (smooth sand, mud, clay, or fine gravel for instance) that cannot be attributed to system noise alone. Speckle is in fact sediment dependent, suggesting that it might be used for sediment classification, but the wide variation of speckle typically encountered within each traditional sediment class must first be overcome. Following a different approach, we use speckle to automatically subdivide the image into just two, much broader classes that are relevant in a search for objects: 1) regions of interest (ROI) where attention is warranted because their pixel-to-pixel variations cannot be attributed to speckle alone---i.e., resolvable seafloor features or distinct objects must be present; and 2) empty regions whose pixel-to-pixel variations are speckle-like and therefore of no interest. The distinction is posed as a hypothesis test based on physical and statistical theory. The test is suited for detecting small targets comprised of few pixels whose intensity and uniformity are unlikely deviations from local speckle statistics.