The automatic recognition of intermodulation, hum and snow noise in cable television systems
A system which automatically monitors the cable television signal is proposed. The monitoring devices, located at key areas in the television network, would alert the cable company to the presence of several important types of television impairments. In this thesis, the automatic detection of three kinds of impairments is discussed; intermodulation carrier beats, hum modulation and snow noise. The detection algorithms we develop are non-intrusive and do not require the use of test signals. A
... test signals. A mathematical model which describes an intermodulation carrier beat is developed and the corresponding 2-dimensional Fourier transform is shown to exhibit properties which are advantageous for automatic recognition. In particular, it is shown that four peaks will appear in the Fourier transform of the image if a beat is present. These peaks possess distinguishing characteristics which allow the automatic detection of the beat. Another television impairment, hum modulation, causes either single or double bands on the television screen depending upon the impairment's frequency. By using the theory of orthogonal functions developed by Sturm and Liouville, a general algorithm is developed which recognizes hum modulation or any impairment of a fixed and known shape. The algorithm is applied to the case of a sinusoidal hum function. Finally, snow noise, which is a random white Gaussian noise, is addressed. An algorithm is developed which detects these random variations by comparing each pixel in the image with neighbouring points. Experimental verification done with several images is shown to produce good results even if the level of noise is small (up to carrier to noise ratio of 35 dB).