Improving Reconstruction Image Quality of Digital Holography Using Median Filter and Intensity Subtraction

2011 ◽  
Vol 48 (12) ◽  
pp. 120901
Author(s):  
王存帅 Wang Cunshuai ◽  
张引科 Zhang Yinke ◽  
郝劲波 Hao Jinbo ◽  
吴艳 Wu Yan
Keyword(s):  
Image Quality ◽  
Digital Holography ◽  
Median Filter ◽  
Reconstruction Image

scholarly journals Implementasi Metode Super Resolusi Untuk Meningkatkan Kualitas Citra Hasil Screenshot

2020 ◽  
Vol 7 (3) ◽  
pp. 432
Author(s):  
Windi Astuti
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Median Filter ◽  
Super Resolution ◽  
Linear Interpolation ◽  
Resolution Method ◽  
Image Zooming ◽  
Image Enlargement ◽  
Three Stages

Various types of image processing that can be done by computers, such as improving image quality is one of the fields that is quite popular until now. Improving the quality of an image is necessary so that someone can observe the image clearly and in detail without any disturbance. An image can experience major disturbances or errors in an image such as the image of the screenshot is used as a sample. The results of the image from the screenshot have the smallest sharpness and smoothness of the image, so to get a better image is usually done enlargement of the image. After the screenshot results are obtained then, the next process is cropping the image and the image looks like there are disturbances such as visible blur and cracked. To get an enlarged image (Zooming image) by adding new pixels or points. This is done by the super resolution method, super resolution has three stages of completion, first Registration, Interpolation, and Reconstruction. For magnification done by linear interpolation and reconstruction using a median filter for image refinement. This method is expected to be able to solve the problem of improving image quality in image enlargement applications. This study discusses that the process carried out to implement image enlargement based on the super resolution method is then built by using R2013a matlab as an editor to edit programs

scholarly journals Penapisan Derau Gaussian, Speckle dan Salt&Pepper Pada Citra Warna

2011 ◽  
Vol 5 (3) ◽  
pp. 29
Author(s):  
Ika Purwanti Ningrum ◽  
Agfianto Eko Putra ◽  
Dian Nursantika
Keyword(s):  
Image Quality ◽  
Digital Image ◽  
Color Image ◽  
Median Filter ◽  
Bilateral Filter ◽  
Filter Method ◽  
Noise Filtering ◽  
Original Image ◽  
Average Filter

Quality of digital image can decrease becouse some noises. Noise can come from lower quality of image recorder, disturb when transmission data process and weather. Noise filtering can make image better becouse will filtering that noise from the image and can improve quality of digital image. This research have aim to improve color image quality with filtering noise. Noise (Gaussian, Speckle, Salt&Pepper) will apply to original image, noise from image will filtering use Bilateral Filter method, Median Filter method and Average Filter method so can improve color image quality. To know how well this research do, we use PSNR (Peak Signal to Noise Ratio) criteria with compared original image and filtering image (image after using noise and filtering noise).This research result with noise filtering Gaussian (variance = 0.5), highest PSNR value found in the Bilateral Filter method is 27.69. Noise filtering Speckle (variance = 0.5), highest PSNR value found in the Average Filter method is 34.12. Noise filtering Salt&Pepper (variance = 0.5), highest PSNR value found in the Median Filter method is 31.27. Keywords— Bilateral Filter, image restoration, derau Gaussian, Speckle dan Salt&Pepper

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 Computational Efficient Method for Denoising of Salt and Pepper Noise for Image Enhancement

2020 ◽  
Vol 8 (6) ◽  
pp. 538-543
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Median Filter ◽  
Noise Removal ◽  
Input Image ◽  
Filter Method ◽  
Pixel Intensity ◽  
Feature Information ◽  
Salt And Pepper

Digital Image processing is basically a computer-algorithm which is used to enhance the quality of image to understand the feature of image and exact the meaningful features information from image. Image processing has wider range of algorithms to be applied to the input image and can escape the difficulty as the signal distortion and add noise in input image at the time of processing of images. Noises affect the image visualization and degraded the image quality, sometimes chaotic variation in value of pixel intensity, lighting effect or because of poor contrast, image can’t be used directly because many time interest feature information not received as output that’s one reason image processing is significant for removal of noise from images, so noise removal is becomes trending field in image processing. Median filter method is one of most popular method to eradicate the effect of noise from image and it enhances the image quality to take meaningful feature easily from image. In this paper removing of noise using median filter to enhance the image quality is discussed, also the importance and applications of enhancement technique are covered. Parameter PSNR and MSE is also used to analysis the image quality along with the visualization of image. Simulation results show that Median filter gives good outcome for salt & pepper noise as compare to other filtering method. MATLAB software is used as simulation tool.

scholarly journals ANALISIS PERBANDINGAN METODE FILTER MEAN, MEDIAN, MAXIMUM, MINIMUM, DAN GAUSSIAN TERHADAP REDUKSI NOISE GAUSSIAN, SALT&PAPPER , SPECKLE, POISSON, DAN LOCALVAR

2019 ◽  
Vol 17 (1) ◽  
pp. 15
Author(s):  
I Gede Aris Gunadi
Keyword(s):  
Image Quality ◽  
Image Restoration ◽  
Median Filter ◽  
Improve Image Quality ◽  
Mean Filter ◽  
The Right ◽  
Influence Of Noise ◽  
Median Maximum ◽  
Maximum Minimum

Due to the influence of noise on an image, the image will experience a decrease in quality.  If the type of noise is known for certain, then the right solution can be determined to restore the condition of an image so that the condition returns to normal. The effort to restore the image condition is stated by image restoration. The most important thing in image restoration is determining the type of noise and the solution for the noise.In this study several types of noise were tried,  gaussian, salt & paper, speckle, poisson, and Localvar on several image samples. In the image that had been exposed to noise, repairs were carried out with several types of filters including gaussian, mean, median, maximum, and minimum. Next was the quality of noise reduction with each filter  determined based on the value of PSNR and MSE. The results of image restoration experiments showed that the mean filter was the best filter used to improve noisegaussian, salt & peppers and speckle image quality. The median filter is the filter that is best used to improve image quality with poisson and localvar noise types.  

scholarly journals Three-Dimensional Reconstruction of Mechanical Parts Based on Digital Holography

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yaohui Dai ◽  
Haiyu Wu ◽  
Gang Zhu ◽  
Yan Yang
Keyword(s):  
Digital Holography ◽  
Optimization Problems ◽  
Three Dimensional ◽  
3D Display ◽  
Mechanical Parts ◽  
First Order ◽  
Reconstruction Image ◽  
Dimensional Reconstruction ◽  
Order Image

In reconstruction of the off-axis digital hologram of diffuse reflection objects, the position of the positive first-order image cannot be accurately obtained because of the low quality of the reconstruction image. This paper focuses on the above problem and proposes a method for marking the first-order image of the 1-FFT surface based on the fast Fourier transform (1-FFT). The parameters of angle of illumination light were investigated, and the maximum relative measurement error is 5.6% by standard objects. The multiaperture stitching technique in cylindrical coordinates is applied to digital holography technology, and the particle swarm optimization algorithm is used to transform the nonlinear equations into optimization problems to solve the splicing parameters. Finally, the 3D display of a typical rotary three-dimensional mechanical part is successfully realized with holography stitching using the above method.

scholarly journals Improving image quality of parallel phase-shifting digital holography

2008 ◽  
Vol 139 ◽  
pp. 012009 ◽  
Author(s):  
Yasuhiro Awatsuji ◽  
Tatsuki Tahara ◽  
Atsushi Kaneko ◽  
Takamasa Koyama ◽  
Kenzo Nishio ◽  
...  
Keyword(s):  
Image Quality ◽  
Digital Holography ◽  
Phase Shifting

scholarly journals Pengaruh Tegangan Tabung terhadap Kualitas Citra pada Pemeriksaan Computed Tomography Kepala menggunakan Iterative Reconstruction

2021 ◽  
Vol 9 (1) ◽  
pp. 103-110
Author(s):  
Muhammad Irsal ◽  
◽  
Nurbaiti Nurbaiti ◽  
Aulia Narendra Mukhtar ◽  
Shinta Gunawati ◽  
...  
Keyword(s):  
Image Quality ◽  
Radiation Dose ◽  
Effective Dose ◽  
Iterative Reconstruction ◽  
Signal To Noise Ratio ◽  
Hounsfield Unit ◽  
P Value ◽  
Dose Length Product ◽  
Reconstruction Image

Iterative reconstruction can optimize radiation dose and improve image quality on CT scan. This research method is quantitative analytic with the analysis of the results of the head CT examination parameters associated with image quality to changes in variations of 80 kV, 100 kV, 120 kV with the use of iterative reconstruction. Image quality measurements are the Hounsfield Unit (HU) value, standard deviation, and Signal to Noise Ratio (SNR) using Radiant Viewers. Effective dose measurement using the Dose Length Product (DLP). Then perform the Kruskal Wallis test to find out whether there is an effect of tube voltage and Iterative Reconstruction on the SNR value using IBM SPSS version 24. The results image quality of the HU value increase due to changes in the kV value, but the value does not change significantly when the iDose changes, for the standard The deviation has decreased due to changes in kV, but the value of the value does not experience a significant change at the time of change in iDose, while SNR increases due to changes in kV value and changes in iDose. The percentage ratio of the effective dose in the use of standard kV with 80 kV decreased radiation dose by 62%, while at 100 kV there was a decrease of 25%, and the use of 120 kV experienced an increase of 25%. The results of the Kruskal Wallis test p-value <0.001, therefore it can be concluded that there is a difference in the SNR image quality at each change in iDose and kV parameters.

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