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	Advances in High-Speed Structured Illumination Microscopy 期刊论文 OAI收割 FRONTIERS IN PHYSICS, 2021, 卷号: 9 作者: Zhao, Tianyu; Wang, Zhaojun; Chen, Tongsheng; Lei, Ming; Yao, Baoli \| 收藏 \| 浏览/下载：65/0 \| 提交时间：2021/06/24 fluorescence microscopy super-resolution SIM hardware acceleration of deep learning image reconstructed algorithm
	Efficient rate control technique for CCSDS image encoding (EI CONFERENCE) 会议论文 OAI收割 IEEE 2nd International Conference on Computing, Control and Industrial Engineering, CCIE 2011, August 20, 2011 - August 21, 2011, Wuhan, China Jin L. 收藏 \| 浏览/下载：95/0 \| 提交时间：2013/03/25 For the limitation of data transmission bandwidth and real time transmission demand generally image compression is required to implement the precise and flexible rate control algorithm. Rate control is an important issue in the image compression field. This paper considers the problem of rate allocation to each encoded segment for CCSDS image compression. One straightforward method is to allocate an equal amount of rate to each segment based on the average of the total number of compressed bytes. The obvious drawback of this method is that different segment will be reconstructed to different quality so the overall quality of the reconstructed image will not be optimized. For the shortage of the original rate control method as to improve the overall quality of the reconstructed image an improved rate control algorithm is proposed for CCSDS image encoding. The key component of the proposed rate control method is the appropriate rate allocation. Experiments on the test images show that the PSNR can be increased at about 0.3dB on average compared to the original algorithm. Therefore experimental results confirm the effectiveness of the proposed algorithm in terms of objective evaluation and the rate-distortion performance of the reconstructed image is improved. 2011 IEEE.
	Multi-focus image fusion algorithm based on adaptive PCNN and wavelet transform (EI CONFERENCE) 会议论文 OAI收割 International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, May 24, 2011 - May 26, 2011, Beijing, China Wu Z.-G.; Wang M.-J.; Han G.-L. 收藏 \| 浏览/下载：78/0 \| 提交时间：2013/03/25 Being an efficient method of information fusion image fusion has been used in many fields such as machine vision medical diagnosis military applications and remote sensing.In this paper Pulse Coupled Neural Network (PCNN) is introduced in this research field for its interesting properties in image processing including segmentation target recognition et al. and a novel algorithm based on PCNN and Wavelet Transform for Multi-focus image fusion is proposed. First the two original images are decomposed by wavelet transform. Then based on the PCNN a fusion rule in the Wavelet domain is given. This algorithm uses the wavelet coefficient in each frequency domain as the linking strength so that its value can be chosen adaptively. Wavelet coefficients map to the range of image gray-scale. The output threshold function attenuates to minimum gray over time. Then all pixels of image get the ignition. So the output of PCNN in each iteration time is ignition wavelet coefficients of threshold strength in different time. At this moment the sequences of ignition of wavelet coefficients represent ignition timing of each neuron. The ignition timing of PCNN in each neuron is mapped to corresponding image gray-scale range which is a picture of ignition timing mapping. Then it can judge the targets in the neuron are obvious features or not obvious. The fusion coefficients are decided by the compare-selection operator with the firing time gradient maps and the fusion image is reconstructed by wavelet inverse transform. Furthermore by this algorithm the threshold adjusting constant is estimated by appointed iteration number. Furthermore In order to sufficient reflect order of the firing time the threshold adjusting constant is estimated by appointed iteration number. So after the iteration achieved each of the wavelet coefficient is activated. In order to verify the effectiveness of proposed rules the experiments upon Multi-focus image are done. Moreover comparative results of evaluating fusion quality are listed. The experimental results show that the method can effectively enhance the edge details and improve the spatial resolution of the image. 2011 SPIE.
	Super-resolution using adaptive blur parameter estimation (EI CONFERENCE) 会议论文 OAI收割 2010 6th International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2010, September 23, 2010 - September 25, 2010, Chengdu, China 作者: Wang H.; Wang H.; Wang H.; Wang H.; Liu G. 收藏 \| 浏览/下载：16/0 \| 提交时间：2013/03/25 Super-resolution is a term for a set of methods of increasing image or video resolution. All these methods are based on the same idea: using information from several images to create one upsized image. In most of the super-resolution algorithms the blur parameter of a LR-image model is always manually set as a default value. In this paper we propose a method to adaptively estimate the blur parameter. We get the initial image of iteration by fusing all low-resolution images. When it is used in MAP algorithm three iterations are enough to get a stable solution. It is greatly reduce the computational power compared with other MAP algorithms. Experiments to real image sequences show that it well preserved the image detail and the reconstructed image is clear. 2010 IEEE.
	Compression of remote sensing image based on Listless Zerotree Coding and DPCM (EI CONFERENCE) 会议论文 OAI收割 ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China Chen S.-L.; Huang L.-Q. 收藏 \| 浏览/下载：32/0 \| 提交时间：2013/03/25 The data quantity of remote sensing image is very large. Furthermore the lowest frequency subband contains the main energy of original image and reflects the coarse of original image after remote sensing image is transformed by wavelet so it is very important to the reconstructed image. Therefore a hybrid image compression method based on Listless Zerotree Coding (LZC) and DPCM is presented namely the lowest frequency subband is compressed by DPCM and others are compressed by LZC. LZC is a kind of zerotree coding algorithm for hardware implementation which is based on SPIHT and substitutes two significant bit maps for three lists in SPIHT algorithm. Thereby LZC significantly reduces the memory requirement and complexity during encoding and decoding procedure. But LZC doesn't recognize the significance of grandchild sets so the PSNR values of LZC are lower than SPIHT's and the compression speed drops. It is improved by adding a significant bit map that recognizes the significance of grandchild sets. A comparison reveals that the PSNR results of the hybrid compression method are 2 dB higher than those of LZC and the compression speed is also improved.
	Study on CCD image compression and mass storage (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者: Liu H.; Liu H.; Liu H. 收藏 \| 浏览/下载：30/0 \| 提交时间：2013/03/25 When CCD camera photographs massive images in the air it is very important to compress and save CCD image timely and validly. This paper designs the CCD image compression and mass storage system. The one part is image compression: this paper introduces a reduced memory still image compression algorithm based on Listless Zerotree Coding (LZC). Compared with SPIHT the approach significantly reduced memory requirement and no reducing the quality of the reconstructed image. The other part is image mass storage: this system uses a kind of special hard disk storage devices that can realize faster data transmission to SCSI (Small Computer System Interface) devices even if it separates oneself from PCs. In the faster data acquisition and storage system data storage is a key technology. Normal approach is saving the data to mass memories and then processing and saving the data after complete acquisition. The continuous acquisition time is restricted with the storage capacity in the normal method so that it can't receive the requirement of CCD image storage on many occasions. While its price will be geminate increasing when we increase the storage capacity. So the approach in this paper is better one to use fast disks on data direct mass storage considering the storage capacity read/write speed and unit cost. The result of the experiment shows that the system has compressed and saved CCD image validly so it reached the anticipative purpose.
	Wavelet packet and neural network basis medical image compression (EI CONFERENCE) 会议论文 OAI收割 4th International Conference on Photonics and Imaging in Biology and Medicine, September 3, 2005 - September 6, 2005, Tianjin, China Zhao X.; Wei J.; Zhai L. 收藏 \| 浏览/下载：21/0 \| 提交时间：2013/03/25 It is difficult to get high compression ratio and good reconstructed image by conventional methods we give a new method of compression on medical image. It is to decompose and reconstruct the medical image by wavelet packet. Before the construction the image use neural network in place of other coding method to code the coefficients in the wavelet packet domain. By using the Kohonen's neural network algorithm not only for its vector quantization feature but also for its topological property. This property allows an increase of about 80% for the compression rate. Compared to the JPEG standard this compression scheme shows better performances (in terms of PSNR) for compression rates higher than 30. This method can get big compression ratio and perfect PSNR. Results show that the image can be compressed greatly and the original image can be recovered well. In addition the approach can be realized easily by hardware.