Method for Improving Reconstructed Image Quality of Digital Hologram Based on SRAD and NSCT

2014 ◽  
Vol 41 (2) ◽  
pp. 0209024
Author(s):  
吴一全 Wu Yiquan ◽  
殷骏 Yin Jun ◽  
朱丽 Zhu Li ◽  
叶志龙 Ye Zhilong
Keyword(s):  
Image Quality ◽  
Reconstructed Image ◽  
Digital Hologram

scholarly journals Time-Division Color Holographic Projection in Large Size Using a Digital Micromirror Device

2021 ◽  
Vol 11 (14) ◽  
pp. 6277
Author(s):  
Takayuki Takahashi ◽  
Tomoyoshi Shimobaba ◽  
Takashi Kakue ◽  
Tomoyoshi Ito
Keyword(s):  
Image Quality ◽  
High Speed ◽  
Reconstructed Image ◽  
Digital Micromirror Device ◽  
Full Color ◽  
Large Size ◽  
Reconstruction Image ◽  
Reduction Methods ◽  
Time Division

Holographic projection is a simple projection as it enlarges or reduces reconstructed images without using a zoom lens. However, one major problem associated with this projection is the deterioration of image quality as the reconstructed image enlarges. In this paper, we propose a time-division holographic projection, in which the original image is divided into blocks and the holograms of each block are calculated. Using a digital micromirror device (DMD), the holograms were projected at high speed to obtain the entire reconstructed image. However, the holograms on the DMD need to be binarized, thereby causing uneven brightness between the divided blocks. We correct this by controlling the displaying time of each hologram. Additionally, combining both the proposed and noise reduction methods, the image quality of the reconstructed image was improved. Results from the simulation and optical reconstructions show we obtained a full-color reconstruction image with reduced noise and uneven brightness.

scholarly journals Pre and Postprocessing for JPEG to Handle Large Monochrome Images

Algorithms ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 255 ◽  
Author(s):  
Walaa Khalaf ◽  
Abeer Al Gburi ◽  
Dhafer Zaghar
Keyword(s):  
Image Quality ◽  
Image Compression ◽  
Compression Ratio ◽  
Rapid Development ◽  
Reconstructed Image ◽  
Hyperbolic Function ◽  
Image Size ◽  
New Techniques ◽  
Large Size

Image compression is one of the most important fields of image processing. Because of the rapid development of image acquisition which will increase the image size, and in turn requires bigger storage space. JPEG has been considered as the most famous and applicable algorithm for image compression; however, it has shortfalls for some image types. Hence, new techniques are required to improve the quality of reconstructed images as well as to increase the compression ratio. The work in this paper introduces a scheme to enhance the JPEG algorithm. The proposed scheme is a new method which shrinks and stretches images using a smooth filter. In order to remove the blurring artifact which would be developed from shrinking and stretching the image, a hyperbolic function (tanh) is used to enhance the quality of the reconstructed image. Furthermore, the new approach achieves higher compression ratio for the same image quality, and/or better image quality for the same compression ratio than ordinary JPEG with respect to large size and more complex content images. However, it is an application for optimization to enhance the quality (PSNR and SSIM), of the reconstructed image and to reduce the size of the compressed image, especially for large size images.

scholarly journals Time-division Color Holographic Projection in Large Size Using a Digital Micromirror Device

2021 ◽  
Author(s):  
Takayuki Takahashi ◽  
Tomoyoshi Shimobaba ◽  
Takashi Kakue ◽  
Tomoyoshi Ito
Keyword(s):  
Image Quality ◽  
High Speed ◽  
Reconstructed Image ◽  
Digital Micromirror Device ◽  
Full Color ◽  
Large Size ◽  
Reconstruction Image ◽  
Reduction Methods ◽  
Time Division

Holographic projection is a simple projection because it enlarges or reduces reconstructed images without using a zoom lens. However, one major problem associated with this projection is the deterioration of image quality as the reconstructed image enlarges. In this paper, we propose a time-division holographic projection, in which the original image is divided into blocks and the holograms of each block are calculated. Using a digital micromirror device (DMD), the holograms were projected at high speed to obtain the entire reconstructed image. However, the holograms on the DMD need to be binarized, thereby causing uneven brightness between the divided blocks. We correct this by controlling the displaying time of each hologram. Additionally, combining both the proposed and noise reduction methods, the image quality of the reconstructed image was improved. Results from the simulation and optical reconstructions show we obtained a full-color reconstruction image with reduced noise and uneven brightness.

scholarly journals Evaluation of the effect of filters on reconstructed image quality from cone beam CT system

2021 ◽  
Vol 11 (1) ◽  
pp. 35-47
Author(s):  
Ngoc Ha Bui ◽  
Tien Hung Bui ◽  
Thuy Duong Tran ◽  
Kim Tuan Tran ◽  
Ngoc Toan Tran
Keyword(s):  
Image Quality ◽  
Cone Beam Ct ◽  
Three Dimensional ◽  
Reconstruction Algorithm ◽  
Reconstructed Image ◽  
Cone Beam ◽  
Spatial Filters ◽  
Dimensional Reconstruction ◽  
Ct System

: 3D Filtered Back Projection (FBP) is a three-dimensional reconstruction algorithm usually used in Cone Beam Computed Tomography (CBCT) system. FBP is one of the most popular algorithms due to its reconstruction is fast while quality of the result is acceptable. It can also handle a more considerable amount of data with same computer performance with other algorithms. However, the quality of a reconstructed image by the FBP algorithm strongly depends on spatial filters and denoising filters applied to projections. In this paper an evaluation of the reconstructed image quality of the CBCT system by using different denoising filters and spatial filters to find out the best filters for the CBCT system is performed. The result shows that, there is a significantly decrease of the noise of projection with the combination of Median and Gaussian filters. The reconstructed image has high resolution with Cosine filter and becomes more sharpen with Hanning filter.

Relationship of Image Quality of Digital Hologram and Grey Level Adjustment

2011 ◽  
Vol 40 (3) ◽  
pp. 327-331
Author(s):  
高志强 GAO Zhiqiang ◽  
李勇 LI Yong
Keyword(s):  
Image Quality ◽  
Grey Level ◽  
Digital Hologram ◽  
Relationship Of

An Improved RNAMC Image Representation

2011 ◽  
Vol 143-144 ◽  
pp. 746-749
Author(s):  
Yun Ping Zheng ◽  
Zu Jia Li ◽  
Mudar Sarem ◽  
Qing Hong Yang ◽  
Xiu Xiu Liao
Keyword(s):  
Image Quality ◽  
Image Representation ◽  
Experimental Results ◽  
Reconstructed Image ◽  
Bit Rate ◽  
Gray Image ◽  
Packing Model ◽  
Representation Method ◽  
Improved Algorithm

In this paper, by controlling the ratio of the length and the width of a homogenous block, we proposed an improved algorithm for the gray image representation by using the Rectangular Non-symmetry and Anti-packing Model Coding (RNAMC) and extended shading approach, which is called the IRNAMC image representation method. Also, we present an IRNAMC representation algorithm of gray images. By comparing our proposed IRNAMC method with the conventional S-Tree Coding (STC) method, the experimental results presented in this paper show that the former can significantly reduce the lower bit rate and the number of homogenous blocks than the latter whereas remaining the satisfactory image quality. Also, the experimental results show that by controlling the ratio of the length and the width, we can improve the reconstructed image quality of the RNAMC method.

A Simple Prediction Method for Progressive Image Transmission

2002 ◽  
pp. 262-272 ◽  
Author(s):  
Chin-Chen Chang ◽  
Guang-Xue Xiao ◽  
Tung-Shou Chen
Keyword(s):  
Image Quality ◽  
Linear Prediction ◽  
Prediction Method ◽  
Image Transmission ◽  
Input Image ◽  
Reconstructed Image ◽  
Progressive Image Transmission ◽  
Intuitive Method

BPM is a simple and intuitive method to implement the progressive image transmission. However, its reconstructed image quality at each of the beginning stages is not good. In this paper, we propose a simple prediction method to improve the quality of the reconstructed image for BPM at each of the beginning stages. By partitioning the input image into smaller blocks, our method transmits an important part of the pixel information of each block to the receiver in each stage. To reconstruct the whole image, the receiver recovers the missing pixel information in each block by linear prediction based on the transmitted pixel information. The experiment results show that our method can significantly improve the reconstructed image quality at each of the beginning stages compared to the BPM and IBPM proposed previously.

scholarly journals SNR of the coded aperture imaging system

2021 ◽  
Vol 28 (1) ◽  
pp. 106-112
Author(s):  
Jianwei Wang ◽  
Yan Zhao
Keyword(s):  
Image Quality ◽  
Imaging System ◽  
Reconstructed Image ◽  
Coded Aperture ◽  
Inverse Filtering ◽  
Light Emitting ◽  
Coded Aperture Imaging ◽  
Imaging Model ◽  
Better Than

AbstractIn this paper, the expression for the SNR has been developed through the imaging model. It is concluded that the image SNR decreases with the increase of the number of light-emitting points of the target under the same hardware conditions and experimental parameters. Using uniform bright squares of different sizes as the target, the SNR of the reconstructed image is calculated. Simulation and prototype experiments have proved the correctness of the conclusion. Based on this conclusion, a method of segmented area imaging is proposed to improve the reconstructed image quality. The quality of all the images using this method with Wiener inverse filtering, R-Lucy deconvolution, and ADMM is better than the image quality obtained by full-area imaging.

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