Restoration and Enhancement of Digitally Reconstructed Holographic Images

Author(s):  
Rajeev Srivastava

Holograms can be reconstructed optically or digitally with the use of computers and other related devices. During the reconstruction phase of a hologram by optical or digital methods, some errors may also be introduced that may degrade the quality of obtained hologram, and may lead to a misinterpretation of the holographic image data, which may not be useful for particular application. The basic common errors are zero-order diffraction and speckle noise. These errors have more undesirable effects in digital than in optical holography because the systems of recording and visualization used in the digital holography are extremely sensitive to them or inclusively increase them. The zero-order diffraction can be removed by using high pass filters with low cut-off frequencies and by subtracting the average intensity of all pixels of the hologram image from the original hologram image. Further, the speckle noise introduced during the formation of digital holographic images, which is multiplicative in nature, reduces the image quality, which may not be suitable for specific applications. As the range of applications get broader, demands toward better image quality increases. Hence, the suppression of noise, higher resolution of the reconstructed images, precise parameter adjustment, and faster, more robust algorithms are the essential issues. In this chapter, the various methods available in literature for enhancement and speckle reduction of digital holographic images have been discussed, and a comparative study of results has been presented.

2017 ◽  
pp. 761-775
Author(s):  
A.S.C.S. Sastry ◽  
P.V.V. Kishore ◽  
Ch. Raghava Prasad ◽  
M.V.D. Prasad

Medical ultrasound imaging has revolutioned the diagnostics of human body in the last few decades. The major drawback of ultrasound medical images is speckle noise. Speckle noise in ultrasound images is because of multiple reflections of ultrasound waves from hard tissues. Speckle noise degrades the medical ultrasound images lessening the visible quality of the image. The aim of this paper is to improve the image quality of ultrasound medical images by applying block based hard and soft thresholding on wavelet coefficients. Medical ultrasound image transformation to wavelet domain uses debauchee's mother wavelet. Divide the approximate and detailed coefficients into uniform blocks of size 8×8, 16×16, 32×32 and 64×64. Hard and soft thresholding on these blocks of approximate and detailed coefficients reduces speckle noise. Inverse transformation to original spatial domain produces a noise reduced ultrasound image. Experiments on medical ultrasound images obtained from diagnostic centers in Vijayawada, India show good improvements to ultrasound images visually. Quality of improved images in measured using peak signal to noise ratio (PSNR), image quality index (IQI), structural similarity index (SSIM).


2021 ◽  
Vol 7 (1) ◽  
pp. 130-134
Author(s):  
Fina Gießler ◽  
Maximilian Thormann ◽  
Bernhard Preim ◽  
Daniel Behme ◽  
Sylvia Saalfeld

Abstract Interdisciplinary exchange of medical datasets between clinicians and engineers is essential for clinical research. Due to the Data Protection Act, which preserves the rights of patients, full anonymization is necessary before any exchange can take place. Due to the continuous improvement of image quality of tomographic datasets, anonymization of patient-specific information is not sufficient. In this work, we present a prototype that allows to reliably obscure the facial features of patient data, thus enabling anonymization of neurological datasets in image space.


Author(s):  
A.S.C.S.Sastry ◽  
P.V.V.Kishore MIEE ◽  
Ch.Raghava Prasad ◽  
M.V.D.Prasad

Medical ultrasound imaging has revolutioned the diagnostics of human body in the last few decades. The major drawback of ultrasound medical images is speckle noise. Speckle noise in ultrasound images is because of multiple reflections of ultrasound waves from hard tissues. Speckle noise degrades the medical ultrasound images lessening the visible quality of the image. The aim of this paper is to improve the image quality of ultrasound medical images by applying block based hard and soft thresholding on wavelet coefficients. Medical ultrasound image transformation to wavelet domain uses debauchee's mother wavelet. Divide the approximate and detailed coefficients into uniform blocks of size 8×8, 16×16, 32×32 and 64×64. Hard and soft thresholding on these blocks of approximate and detailed coefficients reduces speckle noise. Inverse transformation to original spatial domain produces a noise reduced ultrasound image. Experiments on medical ultrasound images obtained from diagnostic centers in Vijayawada, India show good improvements to ultrasound images visually. Quality of improved images in measured using peak signal to noise ratio (PSNR), image quality index (IQI), structural similarity index (SSIM).


Author(s):  
K. Shibatomi ◽  
T. Yamanoto ◽  
H. Koike

In the observation of a thick specimen by means of a transmission electron microscope, the intensity of electrons passing through the objective lens aperture is greatly reduced. So that the image is almost invisible. In addition to this fact, it have been reported that a chromatic aberration causes the deterioration of the image contrast rather than that of the resolution. The scanning electron microscope is, however, capable of electrically amplifying the signal of the decreasing intensity, and also free from a chromatic aberration so that the deterioration of the image contrast due to the aberration can be prevented. The electrical improvement of the image quality can be carried out by using the fascionating features of the SEM, that is, the amplification of a weak in-put signal forming the image and the descriminating action of the heigh level signal of the background. This paper reports some of the experimental results about the thickness dependence of the observability and quality of the image in the case of the transmission SEM.


2001 ◽  
Vol 30 (6) ◽  
pp. 308-313 ◽  
Author(s):  
F Gijbels ◽  
G Sanderink ◽  
C Bou Serhal ◽  
H Pauwels ◽  
R Jacobs

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