The invention discloses an image retrieval method based on manifold learning data compression hash, so as to substantially solve the problems of high memory usage and low retrieval performance in the image retrieval. The method is achieved by the steps as follows: 1, extracting original image characteristics and normalizing the original image characteristics; 2, dividing the normalized data into training data and testing data; 3, compressing the training data to obtain comprehensive compressed data; 4, low-dimensionally embedding the comprehensive compressed data to obtain low-dimensional comprehensive compressed data; 5, respectively obtaining neighborhood relationship matrices among the comprehensive compressed data, the training data and the testing data through an image model; 6, respectively thresholding the arithmetic products among the comprehensive compressed data and two neighborhood relationship matrices to obtain hash codes of the training data and the testing data; and 7, obtaining a retrieval result based on a Hamming distance between the hash code of the training data and the hash code of the testing data. The image retrieval method based on the manifold learning data compression hash reduces the memory usage, and increases the image retrieval performance; and the image retrieval method based on the manifold learning data compression hash is applicable to image search service for Internet of Things and mobile equipment.