Research And Implementation Of Microscopic Imageing And Image Preprocessing Technology

With the increasingly close relationship between computer technology and microscopic imaging technology,more and more intelligent auxiliary diagnosis systems emerge as the times require.As the key technology of intelligent auxiliary diagnosis system,focused imaging and preprocessing technology have also developed rapidly.How to carry out fast focus has been widely concerned,and its application fields are becoming more and more abundant.As a research hotspot in biological morphology,micro image preprocessing technology is the key technology in the recognition decision classification of auxiliary diagnosis system.How to improve the quality of image acquisition and the preprocessing of the target image has become the precondition of the segmentation and recognition processing in the middle and late medical mirror examination.Therefore,this paper focuses on the research and implementation of the research and implementation of microscopic imaging and image preprocessing technology,and studies the key technologies in it,and demonstrates the application value of microscopic images in medical equipment and equipment.The main research work of this paper is to study and analyze microscope imaging and preprocessing technology,and to study and implement focusing imaging,image color migration,image enhancement and so on.The main work is as follows:1.In the field of microscopic imaging,two different focusing algorithms are proposed,which are based on multi target microcell image focusing algorithm and microscopic focusing method based on sparse target images.The two algorithms can focus quickly according to the sparsity of the target in the observation field.It is proved that the focusing effect can be achieved well through the experiment,and it is beneficial to the image processing in the later period.2.The microscopic image normalization is usually influenced by the influence of the collection environment,which is not uniform in the background color,which has a great influence on the segmentation and recognition of the intelligent auxiliary diagnostic equipment.Therefore,it is necessary to make the microcell image normalized in advance.In this paper,an improved Reinhard microscopic image normalization method and a color offset method based on K-means clustering are proposed.The validity of the experiment is proved by comparison experiment.3.In the enhancement of microcellular image,the traditional contrast limited histogram equalization(CLAHE)enhancement algorithm is studied and discussed.A new method of effective enhancement of microcell image based on improved CLAHE is proposed by improving the contrast allocation method and combining with the improved histogram equalization algorithm.Law.This method can enhance the contrast and visual effect while enhancing the texture details of the microcell image.The image obtained by enhanced processing is more suitable for human computer recognition.After many experiments,it is proved that this method has good enhancement effect and adaptability,and can adapt to all kinds of microscopic cell images.