This paper focuses on point target detection with single frame under complicated background and suggests the conception of valid pixel detection. A modified point target detection method based on Markov Random Field was proposed in terms of local correlation of point target and local difference of target and background. This algorithm conducted initial configuration of iterative optimization for MRF by a signal-to-clutter ratio criterion based on complex background separability measure. Moreover, the prior probability model of MRF label field was improved by designing a new prior probability energy function based on Euclidean metric: firstly the label field probability response model of MRF to Euclidean space distance was built; secondly the response ability of the target probability to neighborhood label change was improved by a higher order energy function. The results indicate that: the performance of the detection algorithm in structured background is better; the target’s radiation-dimension detection ability of the modified label field prior probability model is more vigorous compared to the traditional Potts model. The proposed algorithm is a more robust one.