TV cameras are imagers using silicon solid state sensors sensitive to visible and near infrared radiation that generate electronic signal in analog video formats or digital video formats that could be treated as successors of classical old television cameras. Most TV cameras are built nowadays using CCD or CMOS technology. Due to historical reasons TV cameras are often called CCD cameras.

From the point of applications TV cameras can be divided into the presented below groups:

Here we are interested in testing and evaluation of TV cameras used in surveillance applications.   The  cameras from group 5-9 can be potentially used as surveillance TV cameras.  The majority of surveillance TV cameras are low cost CCTV/network cameras designed for short range observation.  Dozens of test methods were proposed for testing these cameras.  As CCTV/network  cameras are low cost devices then the proposed test solutions do not require hi-tech expensive test equipment. We are however interested in testing surveillance TV cameras designed for long range observation, quite often for observation at day/nigh conditions.  Here we are to test quite expensive and important modules of surveillance systems  and professional test equipment is needed for testing these cameras. From now we will understand the term surveillance TV cameras as high-end cameras from group 6-9 with high quality zoom objectives designed for medium/long range observation.

There are some standards that regulate testing low cost surveillance CCTV cameras used in security applications for short range observation. There are standards that regulate testing TV cameras used in machine vision. There is a similar situation with testing of digital still cameras. However, there is no internationally accepted standard that regulates testing and evaluation of surveillance TV cameras designed for medium/long range observation where the most important evaluation criterion is detection, recognition and identification range of target of interest.

In situation of a certain vacuum of legal regulation we use proposed at the end of 1990s (Holst Gerald, CCD Arrays, Cameras, and Displays, JCD Publishing, 1998) a popular concept to extend methodology of the thermal imaging systems performance model FLIR 92 to TV cameras, or wider to all visible imaging systems. If we accept this concept then we can characterize TV cameras using slightly modified parameters, test methods, evaluation methods of thermal imagers. In the latter field testing and evaluation is quite well developed and normalized.

Tab. 1. Comparison of parameters of thermal imagers and parameters of surveillance TV cameras

As we see in Tab. 1 TV cameras can be characterized using similar set of parameters as used to characterize thermal imagers. There are only several differences. First, Minimum Resolvable Contrast characteristic becomes the most important parameter of surveillance TV cameras. Second, Noise Equivalent Input becomes a measure of high frequency temporal noise in TV cameras. Three, two new parameters like sensitivity and SNR are added in case of TV cameras as parameters of such names are used for a long time to characterize these cameras.

Tab. 1. Characteristics of TV cameras

Resolution is typically defined in military standards as maximal spatial frequency of a standard USAF 1951 target that can be revolved by an observer at a certain light level and the target contrast

Minimum Resolvable Contrast function is a function of a minimum contrast difference between the bars of the standard target and the background required to resolve the image of the bars by an observer versus spatial frequency of the target at different levels of target luminance. The USAF 1951 target is used as the standard target during MRC measurement.

In other words MRC is at a resolution measured at different illumination levels for different contrast levels; and the resolution is a point at the MRC characteristic. Having known MRC function it is possible to calculate the ranges of detection, recognition and identification of the target of interest.

MTF is a module from the OTF function of the imaging systems, where OTF is Fourier transform from the image of the point source. In other words, MTF is defined as an output signal modulation to input signal modulation when the signal is sinusoidal wave. It is a measure of the degradation of an output image as correlated to the input pattern which is normalized to 100 percent contrast at zero spatial frequency.

Sensitivity is a minimal illumination value required to produce 50% of the nominal signal at the camera output.

Noise present in signal generated by tested TV imager can be described using different parameters. Here we assume that the noise can be characterized by a set of four parameters:

The presented above set of four noise parameters gives users of TV cameras precision information about influence of noise on overall image quality. In case of designers of TV cameras mode detail information is needed. It is then recommended to use so called 3D noise model where noise is characterized by nine parameters.

Signal to Noise Ratio S/N is a parameter defined as a ratio of the nominal signal at the camera output to the true root-mean-square (rms) value of the signal fluctuations.

Responsivity function is a function that present relationship between output signal generated by tested TV camera (typically in digital levels) on input light intensity (in luminance units or illuminance units). This relationship depends on camera settings: gain, brightness, optics aperture, time exposure, optic aperture etc. Responsivity function is usually S shaped.

Color fidelity is defined as color difference between color of original target and color of its image (parameter applicable only to color TV cameras). Color fidelity is measured using software analysis of images generated by tested TV camera of a reference standard color target under variable illumination conditions.

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