The invention provides a high spectral abnormity detecting method based on dynamic weight deep self-coding and relates to a high spectral abnormity detecting method. The invention aims to settle a problem of low detecting precision caused by partial model pollution by an abnormal model in an existing high spectral abnormity detecting method. The method comprises the steps of 1, obtaining an optimized DBN model; 2, obtaining a coding image and a reconstruction error image; 3, obtaining a local coding image, and performing step 5; 4, obtaining a local reconstruction error set, and performing step 6; 5, obtaining a local distance factor, and performing step 7; 6, obtaining all dynamic weights of the local distance, and performing step 7; and 7, obtaining an abnormity detecting operator value,setting a threshold, and when the abnormity detecting operator value is larger than or equal with the threshold, determining the detected pixel as an abnormal target, and otherwise, determining the tested pixel as a background pixel; taking a next pixel in a detected image as the detected pixel, and performing the steps 3-7 until all pixels in the detected image are determined. The high spectralabnormity detecting method is used for a high spectral abnormity detecting period.