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The reception of the novel by F. M. Dostoevsky “Notes from the Underground” in the works and correspondence of D. H. Lawrence is analyzed in the article. The novelty of the study is in the fact that the influence of this story on Lawrence’s prose is being studied for the first time. Particular attention is paid to Lawrence’s letters to the translator S. S. Kotelyansky, with whom the English writer shared his impressions of reading the works of Russian classics, especially Dostoevsky, as well as to one of the letters addressed to the writer G. Campbell, which contains the only direct reference to “Notes from the Underground” in Lawrence. This letter reveals an individual interpretation of the story by Lawrence. It is proved that this interpretation turns out to be close to the reading of the Notes by L. Shestov. The question is raised about the existing parallels between the text of Dostoevsky and the novels of D. G. Lawrence (“Women in Love”, “The Lost Girl”, “Rainbow” and “Aaron’s Rod”). The similarity is seen in the peculiar interpretation of the Underground concept by Lawrence. It is shown that the image of the Underground in the works of the English writer (usually expressed by the words “underworld”, “subterranean”) is always somehow connected with the irrational principle and is involved in the formation of Lawrence sensualism.

For the problem of low real—time performance of speeded up robust features(SURF) algorithm used in underground video stitching, the SURF algorithm was improved by decreasing dimensions of feature points and extracting feature points only in region of interest. On this basis, an underground video stitching algorithm was proposed.Firstly, feature points of video images are extracted by using the improved SURF algorithm. Then the number of feature points is dynamically tracked. If the number of feature points in the non—first frame image exceeds the threshold, some operations will be performed again including feature point matching and purifying and calculation and storage of projective transformation matrix. Otherwise, the projective transformation matrix from the previous frame is used. Finally, images are fused by gradual weighted average fusion method to generate a stitched video. The experimental results show that the underground video stitching algorithm based on the improved SURF algorithm has high real—time performance and good stitching effect.

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In order to solve problems of traditional image denoising methods such as image blur, edge information loss and so on, an image denoising method based on improved simplified pulse coupled neural network was proposed according to characteristics of underground images including uneven luminosity and large noise. Selection of neurons joining strength β was improved, which made β depend on pixel gray value of image, so as to get better denoising effect. At the same time, selection of decay time constant αE of dynamic threshold was improved, which made αE depend on amplification coefficient vE of threshold output, so as to reduce number of parameters of simplified pulse coupled neural network model. The value of vE was selected through experiment. The experiment results show that the method removes salt and pepper noise of underground images more effectively and preserves details of image edge more completely than traditional median filtering and mean filtering.

For difficult transmission and storage of a large of video monitoring image data of coal mine underground, an image compression method was proposed which was based on improved compressive sending algorithm. Firstly, collected images data are spared by Coiflet2 wavelet transform principle. Secondly, the spared data is measured by measurement matrix to get measurement data. Finally, the images are refactored by orthogonal matching tracking algorithm and inverse transformation. The experimental results show that the method can effectively compress image and reconstruct the image.

Traditional homomorphic filtering function is based on high pass filler, and images processed by the function are dark. The paper analyzed image filtering result by traditional low pass filter at cut-off frequency radius of 5, and got a conclusion that illumination component mainly distributes in low-frequency range of 0~5 radius. It introduced a design scheme of novel homomorphic filter, and proposed a processing method for underground image of uneven illumination based on homomorphic filtering theory. The method uses traditional low pass filter to restrain low-frequency components and traditional high pass filter to strengthen high-frequency components, divides range of low-frequency components of underground images into two sections, and uses different processing methods in the two low-frequency sections, namely restraining low-frequency components in the range of restraining radius of low-frequency and making low-frequency components invariant which are between restraining radius of low-frequency and strengthening radius of high-frequency, so as to avoid restraining low-frequency component overly. The testing result showed that the method solves uneven illumination problem as well as avoids weakening overall illumination of underground images overly, which has good effect.