In wideband spectrum sensing, an unlicensed user determines which portions of a given band have been left idle by the licensed users. A historical deficiency of wideband spectrum sensing, the inability to detect signals with low duty cycle, was addressed in a recent paper, where wideband temporal spectrum sensing was introduced. We propose an algorithm for reliable detection of low duty cycle signals in noisy environments. We leverage this recent advance in wideband spectrum sensing, and apply a well-known edge detection algorithm to determine channel boundaries. Numerical results are presented which show performance improvements over the original wideband temporal spectrum sensing algorithm, particularly in low signal-to-noise ratio scenarios.