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Optical surveys using astronomical telescopes are an efficient way to observe and catalogue space debris, especially for detecting debris in medium or geostationary Earth orbits. Nowadays, small aperture and wide field of view telescopes are widely used and play significant roles in optical space debris surveys. However, special challenges arise since space debris is moving relatively to the background stars and the optics suffer from defects. This affects the efficiency of traditional source extraction methods. Here, a dedicated image processing technique is developed to automatically detect and measure space debris from consecutive CCD images. In order to improve the detection efficiency and robustness, several innovative algorithms are introduced to eliminate noise and increase the object detection ability, and the whole pipeline is optimized to reduce the raw images in real time. A trial survey with a wide field of view and small aperture telescope is presented to test our technique. In our survey, two observing strategies are adopted according to the dynamical features of space objects in the high Earth orbital region, and large numbers of raw CCD images are obtained for both strategies; the efficiency of our reduction is investigated based on the reduction results. Our technique exhibits a correlation rate higher than 97%, and around 400 objects can be routinely observed and catalogued just utilizing one wide field of view telescope in one night. [ABSTRACT FROM AUTHOR]