| 16 matches found in 12 documents. Search time: 0.056 seconds. |
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| Title: Terahertz imaging with compressed sensing and phase retrieval | | Author: Chan WL Moravec ML Baraniuk RG Mittleman DM | | Journal: Opt Lett Citation: V : 33 P : 974-6 Year: 2008 Type: PubMed-not-MEDLINE | | Literature: oryza Field: abstract Doc ID: pub18451957 Accession (PMID): 18451957 | | Abstract: We describe a novel , high-speed pulsed terahertz ( THz ) Fourier imaging system based on compressed sensing ( CS ) , a new signal processing theory , which allows image reconstruction with fewer samples than traditionally required .
Using CS , we successfully reconstruct a 64 x 64 image of an object with pixel size 1 . 4 mm using a randomly chosen subset of the 4096 pixels , which defines the image in the Fourier plane , and observe improved reconstruction quality when we apply phase correction .
For our chosen image , only about 12% of the pixels are required for reassembling the image .
In combination with phase retrieval , our system has the capability to reconstruct images with only a small subset of Fourier amplitude measurements and thus has potential application in THz imaging with cw sources .
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[ Sen. 2, subscore: 2.00 ]: Using CS , we successfully reconstruct a 64 x 64 image of an object with pixel size 1 . 4 mm using a randomly chosen subset of the 4096 pixels , which defines the image in the Fourier plane , and observe improved reconstruction quality when we apply phase correction .
[ Sen. 3, subscore: 1.00 ]: For our chosen image , only about 12% of the pixels are required for reassembling the image .
| | Supplemental links/files: reference in endnote online text related articles pubmed citation | |
Score: 3.00 |
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| Title: Maximum likelihood estimation-based denoising of magnetic resonance images using restricted local neighborhoods .
| | Author: Rajan J Jeurissen B Verhoye M Van Audekerke J Sijbers J | | Journal: Phys Med Biol Citation: V : 56 P : 5221-34 Year: 2011 Type: MEDLINE | | Literature: oryza Field: abstract Doc ID: pub21791732 Accession (PMID): 21791732 | | Abstract: In this paper , we propose a method to denoise magnitude magnetic resonance ( MR ) images , which are Rician distributed .
Conventionally , maximum likelihood methods incorporate the Rice distribution to estimate the true , underlying signal from a local neighborhood within which the signal is assumed to be constant .
However , if this assumption is not met , such filtering will lead to blurred edges and loss of fine structures .
As a solution to this problem , we put forward the concept of restricted local neighborhoods where the true intensity for each noisy pixel is estimated from a set of preselected neighboring pixels .
To this end , a reference image is created from the noisy image using a recently proposed nonlocal means algorithm .
This reference image is used as a prior for further noise reduction .
A scheme is developed to locally select an appropriate subset of pixels from which the underlying signal is estimated .
Experimental results based on the peak signal to noise ratio , structural similarity index matrix , Bhattacharyya coefficient and mean absolute difference from synthetic and real MR images demonstrate the superior performance of the proposed method over other state-of-the-art methods .
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[ Sen. 4, subscore: 2.00 ]: As a solution to this problem , we put forward the concept of restricted local neighborhoods where the true intensity for each noisy pixel is estimated from a set of preselected neighboring pixels .
[ Sen. 7, subscore: 1.00 ]: A scheme is developed to locally select an appropriate subset of pixels from which the underlying signal is estimated .
| | Supplemental links/files: reference in endnote online text related articles pubmed citation | |
Score: 2.00 |
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| Title: A lossless compression scheme for Bayer color filter array images .
| | Author: Chung KH Chan YH | | Journal: IEEE Trans Image Process Citation: V : 17 P : 134-44 Year: 2008 Type: MEDLINE | | Literature: oryza Field: abstract Doc ID: pub18270106 Accession (PMID): 18270106 | | Abstract: In most digital cameras , Bayer color filter array ( CFA ) images are captured and demosaicing is generally carried out before compression .
Recently , it was found that compression-first schemes outperform the conventional demosaicing-first schemes in terms of output image quality .
An efficient prediction-based lossless compression scheme for Bayer CFA images is proposed in this paper .
It exploits a context matching technique to rank the neighboring pixels when predicting a pixel , an adaptive color difference estimation scheme to remove the color spectral redundancy when handling red and blue samples , and an adaptive codeword generation technique to adjust the divisor of Rice code for encoding the prediction residues .
Simulation results show that the proposed compression scheme can achieve a better compression performance than conventional lossless CFA image coding schemes .
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[ Sen. 4, subscore: 2.00 ]: It exploits a context matching technique to rank the neighboring pixels when predicting a pixel , an adaptive color difference estimation scheme to remove the color spectral redundancy when handling red and blue samples , and an adaptive codeword generation technique to adjust the divisor of Rice code for encoding the prediction residues .
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Score: 2.00 |
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| Title: [ Study on application of multi-spectral image texture to discriminating rice categories based on wavelet packet and support vector machine ] | | Author: Chen XJ Wu D He Y Liu S | | Journal: Guang Pu Xue Yu Guang Pu Fen Xi Citation: V : 29 P : 222-5 Year: 2009 Type: In-Process | | Literature: oryza Field: abstract Doc ID: pub19385244 Accession (PMID): 19385244 | | Abstract: Based on multi-spectral digital image texture feature , a new rapid and nondestructive method for discriminating rice categories was put forward .
The new method combined the advantages of wavelet packet and support vector machine ( SVM ) .
In the present study , the images which are 1 036 pixels in vertical direction by 1 , 384 pixels in horizontal direction with 24-bit depth were captured using a red ( R ) waveband , near infrared ( NIR ) waveband and green ( G ) waveband multi-spectral digital imager .
The three wavebands of image ( red , green and NIR ) can be composed into one image which contains more information than images captured by ordinary digital cameras , and the NIR image can catch more information than visible spectrum .
NIR waveband images were decomposed to 16 subbands using three wavelet packet multi-resolution .
Because the main feature of texture information is concentrated on the middle frequency , the 8 subbands of middle frequency were selected to calculate entropy , and the entropy of three wavebands of original image was calculated at the same time .
Eighty images ( twenty for each category ) were used for calibration set and eighty images ( twenty for each category ) were used as the prediction set .
Then the rice categories were classified by SVM .
The classification rate of rice categories was only 93 . 75% using the entropy of original image , but reached 100% by wavelet packet decomposition .
The overall results show that the technique combining wavelet packet and support vector machine can be efficiently utilized for texture recognition of multi-spectra , and is an effective and simple technique for discriminating the rice categories .
This study also provides a foundation for rice grading and other rice industry processing such as quality diction and milling degree .
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[ Sen. 3, subscore: 2.00 ]: In the present study , the images which are 1 036 pixels in vertical direction by 1 , 384 pixels in horizontal direction with 24-bit depth were captured using a red ( R ) waveband , near infrared ( NIR ) waveband and green ( G ) waveband multi-spectral digital imager .
| | Supplemental links/files: reference in endnote online text related articles pubmed citation | |
Score: 2.00 |
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| Title: Comparison between two super-resolution implementations in PET imaging .
| | Author: Chang G Pan T Qiao F Clark JW Jr Mawlawi OR | | Journal: Med Phys Citation: V : 36 P : 1370-83 Year: 2009 Type: In-Process | | Literature: oryza Field: abstract Doc ID: pub19472644 Accession (PMID): 19472644 | | Abstract: Super-resolution ( SR ) techniques are used in PET imaging to generate a high-resolution image by combining multiple low-resolution images that have been acquired from different points of view ( POV ) .
In this article , the authors propose a novel implementation of the SR technique whereby the required multiple low-resolution images are generated by shifting the reconstruction pixel grid during the image reconstruction process rather than being acquired from different POVs The objective of this article is to compare the performances of the two SR implementations using theoretical and experimental studies .
A mathematical framework is first provided to support the hypothesis that the two SR implementations have similar performance in current PET/CT scanners that use block detectors .
Based on this framework , a simulation study , a point source study , and a NEMA/IEC phantom study were conducted to compare the performance of these two SR implementations with respect to contrast , resolution , noise , and SNR .
For reference purposes , a comparison with a native reconstruction ( NR ) image using a high-resolution pixel grid was also performed .
The mathematical framework showed that the two SR implementations are expected to achieve similar contrast and resolution but different noise contents .
These results were confirmed by the simulation and experimental studies .
The simulation study showed that the two SR implementations have an average contrast difference of 2 . 3% , while the point source study showed that their average differences in contrast and resolution were 0 . 5% and 1 . 2% , respectively .
Comparisons between the SR and NR images for the point source study showed that the NR image exhibited averages of 30% and 8% lower contrast and resolution , respectively .
The NEMA/IEC phantom study showed that the three images ( two SR and NR ) exhibited different noise structures .
The SNR of the new SR implementation was , on average , 21 . 5% lower than the original implementation largely due to an increase in background noise , while the NR image had averages of 18 . 5% and 8% lower SNR and contrast , respectively , versus the two SR images .
The new SR implementation can potentially replace the original SR approach in current PET scanners that use block detectors while maintaining similar contrast and resolution , but at a relatively lower SNR .
A major advantage of the new SR implementation is its shorter overall scan duration which results in an increase in scanner throughput and a reduction in patient motion .
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[ Sen. 2, subscore: 1.00 ]: In this article , the authors propose a novel implementation of the SR technique whereby the required multiple low-resolution images are generated by shifting the reconstruction pixel grid during the image reconstruction process rather than being acquired from different POVs The objective of this article is to compare the performances of the two SR implementations using theoretical and experimental studies .
[ Sen. 5, subscore: 1.00 ]: For reference purposes , a comparison with a native reconstruction ( NR ) image using a high-resolution pixel grid was also performed .
| | Supplemental links/files: reference in endnote online text related articles pubmed citation | |
