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The determination of channel characteristics has always been a research hotspot of wireless communication systems. It directly affects the correctness of channel state analysis. Channel feature extraction methods are endless, but most of the existing extraction methods are limited by specific environments. The methods are complex, the system analysis is not comprehensive enough, the applicability is not extensive, and it is affected by external interference. This paper avoids the disadvantages of direct extraction and innovatively introduces an image construction method that can analyze the channel state in real time. In addition, an improved image feature extraction algorithm is proposed for the state images proposed in this paper, which verifies high robust performance of the algorithm. In the end, a model capable of efficiently and accurately predicting real-time conditions of short-wave fading channel states is constructed. First, channel state images are constructed, including time domain image, frequency domain image, and related domain image. The three state images reflect the channel state in all aspects. Then, the multi-texton image feature extraction method is optimized and improved, and the multi-structure color difference (MSC) extraction method is constructed to extract the channel state image information. Then, through the experimental simulation, the method of channel state division is specified, and the performance advantage of the improved algorithm MSC relative to the original algorithm is verified. Finally, discriminating channel state based on SVM algorithm. A series of experiments on rotation invariance test, immunity from interference test and illumination variation test verify that the proposed method has high robustness and the recognition accuracy is between 80% and 100%, which can effectively identify Instantaneous channel advantages and disadvantages.