44,766 research outputs found
Enhancement of Image Resolution by Binarization
Image segmentation is one of the principal approaches of image processing.
The choice of the most appropriate Binarization algorithm for each case proved
to be a very interesting procedure itself. In this paper, we have done the
comparison study between the various algorithms based on Binarization
algorithms and propose a methodologies for the validation of Binarization
algorithms. In this work we have developed two novel algorithms to determine
threshold values for the pixels value of the gray scale image. The performance
estimation of the algorithm utilizes test images with, the evaluation metrics
for Binarization of textual and synthetic images. We have achieved better
resolution of the image by using the Binarization method of optimum
thresholding techniques.Comment: 5 pages, 8 figure
Multipass holographic interferometer improves image resolution
Multipass holographic interferometer forms a hologram of high diffraction efficiency, and hence provides a bright and high contrast interferogram. It is used to study any effect which changes the index of refraction and to study surface deformations of a flat reflecting surface
Image resolution enhancement using dual-tree complex wavelet transform
In this letter, a complex wavelet-domain image resolution enhancement algorithm based on the estimation of wavelet coefficients is proposed. The method uses a forward and inverse dual-tree complex wavelet transform (DT-CWT) to construct a high-resolution (HR) image from the given low-resolution (LR) image. The HR image is reconstructed from the LR image, together with a set of wavelet coefficients, using the inverse DT-CWT. The set of wavelet coefficients is estimated from the DT-CWT decomposition of the rough estimation of the HR image. Results are presented and discussed on very HR QuickBird data, through comparisons between state-of-the-art resolution enhancement methods
Optimal Addition of Images for Detection and Photometry
In this paper we describe weighting techniques used for the optimal
coaddition of CCD frames with differing characteristics. Optimal means maximum
signal-to-noise (s/n) for stellar objects. We derive formulae for four
applications: 1) object detection via matched filter, 2) object detection
identical to DAOFIND, 3) aperture photometry, and 4) ALLSTAR profile-fitting
photometry. We have included examples involving 21 frames for which either the
sky brightness or image resolution varied by a factor of three. The gains in
s/n were modest for most of the examples, except for DAOFIND detection with
varying image resolution which exhibited a substantial s/n increase. Even
though the only consideration was maximizing s/n, the image resolution was seen
to improve for most of the variable resolution examples. Also discussed are
empirical fits for the weighting and the availability of the program, WEIGHT,
used to generate the weighting for the individual frames. Finally, we include
appendices describing the effects of clipping algorithms and a scheme for
star/galaxy and cosmic ray/star discrimination.Comment: 27 pages (uuencoded compressed postscript), 199
An optimal factor analysis approach to improve the wavelet-based image resolution enhancement techniques
The existing wavelet-based image resolution enhancement techniques have many assumptions, such as limitation of the way to generate low-resolution images and the selection of wavelet functions, which limits their applications in different fields. This paper initially identifies the factors that effectively affect the performance of these techniques and quantitatively evaluates the impact of the existing assumptions. An approach called Optimal Factor Analysis employing the genetic algorithm is then introduced to increase the applicability and fidelity of the existing methods. Moreover, a new Figure of Merit is proposed to assist the selection of parameters and better measure the overall performance. The experimental results show that the proposed approach improves the performance of the selected image resolution enhancement methods and has potential to be extended to other methods
Can small be beautiful? assessing image resolution requirements for mobile TV
Mobile TV services are now being offered in several countries, but for cost reasons, most of these services offer material directly recoded for mobile consumption (i.e. without additional editing). The experiment reported in this paper, aims to assess the image resolution and bitrate requirements for displaying this type of material on mobile devices. The study, with 128 participants, examined responses to four different image resolutions, seven video encoding bitrates, two audio bitrates and four content types. The results show that acceptability is significantly lower for images smaller than 168×126, regardless of content type. The effect is more pronounced when bandwidth is abundant, and is due to important detail being lost in the smaller screens. In contrast to previous studies, participants are more likely to rate image quality as unacceptable when the audio quality is high
Fast Compressive 3D Single-pixel Imaging
In this work, we demonstrate a modified photometric stereo system with perfect pixel
registration, capable of reconstructing continuous real-time 3D video at ~8 Hz for 64 x 64 image resolution by employing evolutionary compressed sensing
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