This paper presents a new representation for image classification based on spatial correlogram approach. Spatial correlogram captures spatial co-occurrences of pairwise codewords. This representation augments traditional bag-of-features model by adding spatial information into it and compresses the information contained in a correlogram without loss of discriminative power. For the purpose of increasing classification accuracy, we combine the correlogram with spatial pyramid. In a number of image classification experiments, we find that, the proposed method reaches good performance and high accuracy.