A method for correcting an image, comprising: obtaining, by a front end device of a video monitoring system, a white region for performing automatic white balance, wherein, the white region represents a distribution of color responses of a white object under different color temperatures in a chromaticity space; generating, by the front end device, at least one cluster by clustering statistical points within the white region of a to-be-detected image which is captured by the video monitoring system; in case that the number of statistical points within one of said clusters is greater than a preset threshold, determining, by the front end device, the cluster as a target cluster, and determining, by the front end device, the statistical points within the target cluster as white points; and determining, by the front end device, a white balance gain of the to-be-detected image based on the target cluster, correcting, by the front end device, the to-be-detected image based on the determined white balance gain, wherein the white region comprises a plurality of sub-regions, and clustering the statistical points within the white region of the to-be-detected image comprises: determining, by the front end device, the number of statistical points within each of the sub-regions; and generating, by the front end device, at least one cluster from the plurality of sub-regions according to a density-based spatial clustering algorithm which takes a center of each of the sub-regions as a clustering object and takes the number of statistical points within each of the sub-regions as a density of the clustering object. obtaining, by a front end device of a video monitoring system, a white region for performing automatic white balance, wherein, the white region represents a distribution of color responses of a white object under different color temperatures in a chromaticity space; generating, by the front end device, at least one cluster by clustering statistical points within the white region of a to-be-detected image which is captured by the video monitoring system; in case that the number of statistical points within one of said clusters is greater than a preset threshold, determining, by the front end device, the cluster as a target cluster, and determining, by the front end device, the statistical points within the target cluster as white points; and determining, by the front end device, the cluster as a target cluster, and determining, by the front end device, the statistical points within the target cluster as white points; and determining, by the front end device, a white balance gain of the to-be-detected image based on the target cluster, correcting, by the front end device, the to-be-detected image based on the determined white balance gain, wherein the white region comprises a plurality of sub-regions, and clustering the statistical points within the white region of the to-be-detected image comprises: determining, by the front end device, the number of statistical points within each of the sub-regions; and generating, by the front end device, at least one cluster from the plurality of sub-regions according to a density-based spatial clustering algorithm which takes a center of each of the sub-regions as a clustering object and takes the number of statistical points within each of the sub-regions as a density of the clustering object. determining, by the front end device, the number of statistical points within each of the sub-regions; and generating, by the front end device, at least one cluster from the plurality of sub-regions according to a density-based spatial clustering algorithm which takes a center of each of the sub-regions as a clustering object and takes the number of statistical points within each of the sub-regions as a density of the clustering object. <EOS>