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4th IEEE International Conference on Applied System Invention (IEEE ICASI)

作者： Zou, Jiancheng Song, Rui North China Univ Technol Inst Image Proc & Pattern Recognit 5 Jinyuanzhuang Rd Beijing Peoples R China

ISBN: (纸本)9781538643426

A novel method of image segmentation based on Faster-RCNN and microarray camera (3 x 3) is proposed in this paper, we use the microarray camera to obtain nine images in the same scene and use nine array images to achieve image segmentation. Through the microarray camera, we can obtain images quickly. The result of microarray camera and high-speed camera is similar, the shooting interval is short and the disparity information between array images is small. We use the Faster-RCNN algorithm and the GrabCut algorithm to segment target for the array images. Because of the size of microarray camera is small, it can be widely used on portable devices in the further. In comparison to Faster-RCNN network, the experimental results show that the proposed method is more efficient.

关键词： microarray camera Image Segmention Faster-RCNN

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A novel enhancement method for low illumination images based on microarray camera

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Applied Mathematics(A Journal of Chinese Universities) 2017年第3期32卷 313-322页

作者： ZOU Jian-cheng ZHENG Wen-qi YANG Zhi-hui Institute of Image Processing and Pattern Recognition North China University of Technology Beijing 100144 China.

It is difficult but important to get clear information from the low illumination images. In recent years the research of the low illumination image enhancement has become a hot topic in image processing and computer vision. The Retinex algorithm is one of the most popular methods in the field and uniform illumination is necessary to enhance low illumination image quality by using this algorithm. However, for the different areas of an image with contrast brightness differences, the illumination image is not smooth and causes halo artifacts so that it cannot retain the detail information of the original images. To solve the problem, we generalize the multi-scale Retinex algorithm and propose a new enhancement method for the low illumination images based on the microarray camera. The proposed method can well make up for the deficiency of imbalanced illumination and significantly inhibit the halo artifacts as well. Experimental results show that the proposed method can get better image enhancement effect compared to the multi-scale Retinex algorithm of a single image enhancement. Advantages of the method also include that it can significantly inhibit the halo artifacts and thus retain the details of the original images, it can improve the brightness and contrast of the image as well. The newly developed method in this paper has application potential to the images captured by pad and cell phone in the low illumination environment.

关键词： low illumination microarray camera multi-scale Retinex image sharpening

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A Novel Image Segmentation Algorithm Based on the microarray camera and Modified YCrCb Color Space 1

A Novel Image Segmentation Algorithm Based on the Microarray...

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1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)

作者： Zou, Jiancheng Song, Rui Chen, Tianshu North China Univ Technol Inst Image Proc & Pattern Recognit 5 Jinyuanzhuang Rd Beijing Peoples R China

ISBN: (纸本)9781538652671

A novel method of image segmentation based on microarray camera (3 x 3) and modified YCrCb color space is proposed in this paper, we use the microarray camera to obtain array images in the same scene and use array images to achieve image segmentation. microarray camera can take wider field of vision and contain more image details than traditional cameras. Using the SSD network to detect the object in the array images and using modified YCrCb color space to improve the accuracy under the high light intensity. The microarray lens in this paper is expected to be applied to mobile phones and tablet devices. Experimental results show that the proposed algorithm reduces the error rate and the edge extraction is more complete and smoother compared with SSD network.

关键词： Image segmentation SSD YCrCb color space microarray camera

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Super-Resolution Reconstruction of Images Based on microarray camera

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CMC-COMPUTERS MATERIALS & CONTINUA 2019年第1期60卷 163-177页

作者： Zou, Jiancheng Li, Zhengzheng Guo, Zhijun Hong, Don North China Univ Technol Coll Sci Beijing 100144 Peoples R China Middle Tennessee State Univ Dept Math Sci Murfreesboro TN 37132 USA

In the field of images and imaging, super-resolution (SR) reconstruction of images is a technique that converts one or more low-resolution (LR) images into a high-resolution (HR) image. The classical two types of SR methods are mainly based on applying a single image or multiple images captured by a single camera. microarray camera has the characteristics of small size, multi views, and the possibility of applying to portable devices. It has become a research hotspot in image processing. In this paper, we propose a SR reconstruction of images based on a microarray camera for sharpening and registration processing of array images. The array images are interpolated to obtain a HR image initially followed by a convolution neural network (CNN) procedure for enhancement. The convolution layers of our convolution neural network are 3 x 3 or 1 x 1 layers, of which the 1 x 1 layers are used to improve the network performance particularly. A bottleneck structure is applied to reduce the parameter numbers of the nonlinear mapping and to improve the nonlinear capability of the whole network. Finally, we use a 3 x 3 deconvolution layer to significantly reduce the number of parameters compared to the deconvolution layer of FSRCNN-s. The experiments show that the proposed method can not only ameliorate effectively the texture quality of the target image based on the array images information, but also further enhance the quality of the initial high resolution image by the improved CNN.

关键词： Super-resolution reconstruction microarray camera convolution neural network

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Depth information acquisition and image measurement algorithm using microarray camera

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INTERNATIONAL JOURNAL OF AUTONOMOUS AND ADAPTIVE COMMUNICATIONS SYSTEMS 2023年第5期16卷 419-435页

作者： Zou, Jiancheng Yan, Peizhou Li, Zhengzheng North China Univ Technol Beijing Key Lab Urban Rd Traff Intelligent Control Beijing 100043 Peoples R China

The traditional algorithm for obtaining the depth information of an image is a binocular stereo vision algorithm. Meanwhile, the multi-eye stereo vision system can obtain more scene information. Based on the 3 x 3 array lens, we obtained the depth information of static and dynamic scenes and applied the depth map to image measurement. First, the single calibration of 9 sub-lenses and the stereo calibration of each lens with the central lens are carried out. Second, a corresponding energy cost function is established to construct a Markov random field. Then, the graph-cutting algorithm is applied to minimise the energy function, select the optimal matching value, and then to get the matching graph with depth information. Finally, the measurement of the target in the scene is obtained based on the depth map. The experimental results show that the proposed method can get more accurate depth information than monocular and binocular cameras.

关键词： microarray camera Markov random field graph cut depth information image measurement

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