A detection technique based on a synergistic composition of wavelet feature detectors is demonstrated on sonar imaging data. The wavelets are used to preprocess the imagery for enhancing highlights and shadows. A neural network is trained on the preprocessed imagery to weight the output of two filters for underwater object detection. This approach is demonstrated on multiple scales. Results indicate this composite approach is highly effective.