Partial Pixel Research Articles

Effective Revisable Data Hiding in Encrypted Image for Protection of Image Content

In this article, we propose a reversible method for hiding data, in which the original image and hidden data can be restored on the receiving side. The owner encrypts the original image using an encryption key to protect the privacy of the image content. Each block of encrypted image is added to the little secret by Hider data using the key data hiding. Data hiding process causes only a small change in each partial pixel flip block, which improves decoded image visual quality. The image can be easily decoded receiver using the key, data encryption key to hide the adaptive soft characteristic of the evaluation function along the direction of the isophote, the secret data can be extracted from a decoded image and original image recovery can be restored more successfully.

Estimating Digital Watermark Synchronization Signal Using Partial Pixel Least Squares

To read a digital watermark from printed images requires that the watermarking system read correctly after affine distortions. One way to recover from affine distortions is to add a synchronization signal in the Fourier frequency domain and use this synchronization signal to estimate the applied affine distortion. If the synchronization signal contains a collection of frequency impulses, then a least squares match of frequency impulse locations results in a reasonably accurate linear transform estimation. Nearest neighbor frequency impulse peak location estimation provides a good rough estimate for the linear transform, but a more accurate refinement of the least squares estimate is accomplished with partial pixel peak location estimates. In this paper we will show how to estimate peak locations to any desired accuracy using only the complex frequencies computed by the standard DFT. We will show that these improved peak location estimates result in a more accurate linear transform estimate. We conclude with an assessment of detector robustness that results from this improved linear transformation accuracy.

Evaluation of Popular Photometry Analysis Softwares Using DSLR Camera

The Digital Single Lens Reflex (DSLR) camera combined with a small aperture telescope is an efficient equipment for an astronomy-related lab exercise. This paper compares the different photometry softwares to provide insights on using the GUI-based photometry tool to the conventional command-line based photometry tool. The magnitude of the same point source measured within the aperture is consistent regardless of the software used although the background estimation, partial pixel treatment, and error estimation are slightly different. In a crowded field image where the aperture photometry is less reliable, the aperture photometry with varying aperture size is useful to see the qualitative trend for the magnitude. Due to the variation in ISO settings and the color dependence on the RGB Bayer system, an initial uncertainty of ~0.15mag is expected to be embedded in the magnitude derived from the DSLR images.

Improving Super-Resolution Mapping by Combining Multiple Realizations Obtained Using the Indicator-Geostatistics Based Method

Indicator-geostatistics based super-resolution mapping (IGSRM) is a popular super-resolution mapping (SRM) method. Unlike most existing SRM methods that produce only one SRM result each, IGSRM generates multiple equally plausible super-resolution realizations (i.e., SRM results). However, multiple super-resolution realizations are not desirable in many applications, where only one SRM result is usually required. These super-resolution realizations may have different strengths and weaknesses. This paper proposes a novel two-step combination method of generating a single SRM result from multiple super-resolution realizations obtained by IGSRM. In the first step of the method, a constrained majority rule is proposed to combine multiple super-resolution realizations generated by IGSRM into a single SRM result under the class proportion constraint. In the second step, partial pixel swapping is proposed to further improve the SRM result obtained in the previous step. The proposed combination method was evaluated for two study areas. The proposed method was quantitatively compared with IGSRM and Multiple SRM (M-SRM), an existing multiple SRM result combination method, in terms of thematic accuracy and geometric accuracy. Experimental results show that the proposed method produces SRM results that are better than those of IGSRM and M-SRM. For example, in the first example, the overall accuracy of the proposed method is 7.43–10.96% higher than that of the IGSRM method for different scale factors, and 1.09–3.44% higher than that of the M-SRM, while, in the second example, the improvement in overall accuracy is 2.42–4.92%, and 0.08–0.90%, respectively. The proposed method provides a general framework for combining multiple results from different SRM methods.

Long-term trend of Ulva prolifera blooms in the western Yellow Sea

Blooms of the green macroalga Ulva prolifera in the western Yellow Sea occurred every year since 2008, and they have been reported and studied extensively using a variety of means including remote sensing. However, to date, long-term bloom patterns have not been reported except for a few case studies showing examples in different years. Here, using MODIS observations and an objective method to perform statistical analysis, mean Ulva coverage in the western Yellow Sea has been derived and analyzed between 2007 and 2015 at both monthly and annual scales. On annual scale, mean Ulva coverage decreased after 2008, but increased rapidly after 2012 from 8km2 in 2012 to 116km2 in 2015 (the largest ever reported in history for this region). In the month of June the mean coverage increased from 18km2 in 2012 to 363km2 in 2015. Other than 2009 and 2010, the month of June showed maximum Ulva coverage in every year. These coverage estimates are significantly lower than previously reported values as they represent “pure” algae coverage after taking into account of partial pixel coverage. Several environmental factors were examined in an attempt to determine the reasons behind such long-term changes, yet the results are inconclusive, suggesting a strong necessity of further coordinated and multi-disciplinary researches.

Automatic Articular Cartilage Segmentation Based on Pattern Recognition from Knee MRI Images.

An automatic method for cartilage segmentation using knee MRI images is described. Three binary classifiers with integral and partial pixel features are built using the Bayesian theorem to segment the femoral cartilage, tibial cartilage and patellar cartilage separately. First, an iterative procedure based on the feedback of the number of strong edges is designed to obtain an appropriate threshold for the Canny operator and to extract the bone-cartilage interface from MRI images. Second, the different edges are identified based on certain features, which allow for different cartilage to be distinguished synchronously. The cartilage is segmented preliminarily with minimum error Bayesian classifiers that have been previously trained. According to the cartilage edge and its anatomic location, the speed of segmentation is improved. Finally, morphological operations are used to improve the primary segmentation results. The cartilage edge is smooth in the automatic segmentation results and shows good consistency with manual segmentation results. The mean Dice similarity coefficient is 0.761.

Automated detection and quantitative assessment of pulmonary airways depicted on CT images

We developed and tested a fully automated computerized scheme that identifies pulmonary airway sections depicted on computed tomography (CT) images and computes their sizes including the lumen and airway wall areas. The scheme includes four processing modules that (1) segment left and right lung areas, (2) identify airway locations, (3) segment airway walls from neighboring pixels, and (4) compute airway sizes. The scheme uses both a raster scanning and a labeling algorithm complemented by simple classification rules for region size and circularity to automatically search for and identify airway sections of interest. A profile tracking method is used to segment airway walls from neighboring pixels including those associated with dense tissue (i.e., pulmonary arteries) along scanning radial rays. A partial pixel membership method is used to compute airway size. The scheme was tested on ten randomly selected CT studies that included 26 sets of CT images acquired using both low and conventional dose CT examinations with one of four reconstruction algorithms (namely, "bone," "lung," "soft," and "standard" convolution kernels). Three image section thicknesses (1.25, 2.5, and 5 mm) were evaluated. The scheme detected a large number of quantifiable airway sections when the CT images were reconstructed using high spatial frequency convolution kernels. The detection results demonstrated a consistent trend for all test image sets in that as airway lumen size increases, on average the airway wall area increases as well and the wall area percentage decreases. The study suggested that CT images reconstructed using high spatial frequency convolution kernels and thin-section thickness were most amenable to automated detection, reasonable segmentation, and quantified assessment when the airways are close to being perpendicular to the CT image plane.

SU‐FF‐I‐21: Two‐Dimensional Shift‐And‐Add (SAA) Algorithm for Digital Breast Tomosynthesis Reconstruction

Purpose: To investigate a two‐dimensional Shift‐And‐Add algorithm for three‐dimensional digital breast tomosynthsis reconstruction to correct for defects existing in the traditional Shift‐And‐Add algorithm that calculates only one‐dimensional shift amount along the axis of x‐ray tube's motion. Method and Materials: With the traditional Shift‐And‐Add (SAA) algorithm for breast tomosynthesis reconstruction, shift amounts for each projection plane are calculated only along the axis of x‐ray tube's movement. As a result, small objects such as microcalcifications appear slightly blurred in the direction perpendicular to the direction of tube motion. In this project, a two‐dimensional SAA method was developed to correct for this phenomenon. Shift amounts for every pixel location on each reconstruction plane were computed, taking into account the 2D arc projection location of reconstructed objects in each plane. Bilinear interpolation was used for partial pixel locations. Impulses at different 3‐D locations were simulated and a few human subject tomosynthesis sequences were acquired for investigation. Results: Two‐dimensional SAA demonstrated the improvement in the direction that is perpendicular to the tube motion direction. For human subjects, the appearance of calcifications from 2D SAA was sharper than traditional SAA at the direction orthogonal to the tube motion direction. The out‐of‐plane artifacts of calcifications changed from curved to be straight. Conclusion: Two‐dimensional SAA is an effective method to reconstruct 3D tomosynthesis images of the breast. Compared with the traditional SAA, the new method corrects for 2D shift amounts coming from the isocentric tube motion. This provides more accurate and reliable results compared with other SAA algorithms. Conflict of Interest: Research sponsored in part by a research grant from Siemens Medical Solutions.

MPEG-2 Motion Estimation using a PC Cluster

Motion estimation is the most computing-intensive component of the MPEG-2 encoding process. It refers to the action of searching for the closest prediction of a certain image block. The more accurate the prediction, the better the achieved compression and quality are. The optimal solution is guaranteed by performing an exhaustive search for all possible predictions for a certain block. The motion estimation component is characterized by a polynomial time, and is responsible for about 90% of the encoding time. In this article the search time is reduced by parallelizing the block matching search algorithm, used in addition to the partial distance method to prevent useless but time-expensive calculations. Partial distance and pixel spiral summation order are used to reduce the time spent on error summation. Experimental results show that significant improvements in performance can be made. The encoding time using a 128 × 128 window is reduced from 14 sec/frame, in the sequential case, to 3.2 sec/frame, about five times faster, using six Pentium 450 MHz in parallel.

Mpeg-2 Motion Estimation Using a PC Cluster

Motion estimation is the most computing-intensive component of the MPEG-2 encoding process. It refers to the action of searching for the closest prediction of a certain image block. The more accurate the prediction, the better the achieved compression and quality are. The optimal solution is guaranteed by performing an exhaustive search for all possible predictions for a certain block. The motion estimation component is characterized by a polynomial time, and is responsible for about 90% of the encoding time. In this article the search time is reduced by parallelizing the block matching search algorithm, used in addition to the partial distance method to prevent useless but time-expensive calculations. Partial distance and pixel spiral summation order are used to reduce the time spent on error summation. Experimental results show that significant improvements in performance can be made. The encoding time using a 128 x 128 window is reduced from 14 sec/frame, in the sequential case, to 3.2 sec/frame, about five times faster, using six Pentium 450 MHz in parallel.

Evaluation of CsI(Tl)-PIN diode array tiling schemes

Methods of tiling scintillator-photodiode detector arrays were investigated. Si photodiodes coupled to CsI(Tl) scintillation crystals are being considered for high-resolution (/spl sim/1 mm) gamma-ray imaging. Large area (/spl sim/200 cm/sup 2/) detectors can be assembled by tiling together modular arrays. The goal of the tiling schemes was to maintain uniform pixel pitch and detector performance across the seam where the arrays join. The perimeter of the array has an insensitive area that can be an appreciable fraction of a pixel size when using 1 mm pixels. One tiling scheme used smaller pixels at the edge of the arrays to compensate for this insensitive area (partial PIN method). A second approach used a scintillator light-sharing technique to cover the insensitive area (segmented method). The partial pixel method resulted in worse energy resolution and sensitivity in the partial pixels compared to the full pixels (20% and 30% FWHM at 140 keV for edge and corner pixels, respectively, versus 12% in full pixels, with relative corner pixel sensitivity of /spl sim/50%), but successfully maintained spatial resolution and pixel pitch. The segmented crystal light-sharing method demonstrated 17%-20% FWHM energy resolution (at 140 keV) in the edge pixels, /spl sim/85% relative sensitivity, and provided good pixel identification (i.e., good spatial resolution). However, the segmented crystal method is considerably more complex to implement, compared with the partial pixel method.

Real-time full-color three-dimensional display with a micromirror array

We designed, realized, and tested what is believed to be the first real-time, full-color, autostereoscopic three-dimensional (3-D) display with a micromirror array. Compared with the diffractive partial pixel architecture [Opt. Lett. 20, 1418 (1995)], this approach has certain advantages:(1) Micromirrors are reflective and thus achromatic (panchromatic) and (2) a variety of displays can be used as the image source. We used backlit transparencies to test the system and then used an ordinary color CRT to show several computer-generated full-color 3-D animations.

Three‐dimensional display utilizing a diffractive optical element and an active matrix liquid crystal display

We describe the design, construction, and performance of the first real-time autostereoscopic three-dimensional (3-D) display based on the partial pixel 3-D display architecture. The primary optical components of the 3-D display are an active-matrix liquid crystal display and a diffractive optical element (DOE). The display operates at video frame rates and is driven with a conventional VGA signal. Three-dimensional animations with horizontal motion parallax are readily viewable as sets of stereo images. Formation of the virtual viewing slits by diffraction from the partial pixel apertures is experimentally verified. The measured contrast and perceived brightness of the display are excellent, but there are minor flaws in image quality due to secondary images. The source of these images and how they may be eliminated is discussed. The effects of manufacturing-related systematic errors in the DOE are also analyzed.

Liquid crystal-on-silicon implementation of the partial pixel three-dimensional display architecture

We report the implementation of a liquid crystal-on-silicon, three-dimensional (3-D) diffractive display based on the partial pixel architecture. The display generates multiple stereoscopic images that are perceived as a static 3-D scene with one-dimensional motion parallax in a manner that is functionally equivalent to a holographic stereogram. The images are created with diffraction gratings formed in a thin liquid crystal layer by fringing electric fields from transparent indium tin oxide interdigitated electrodes. The electrodes are controlled by an external drive signal that permits the 3-D scene to be turned on and off. The display has a contrast ratio of 5.8, which is limited principally by optical scatter caused by extraneous fringing fields. These scatter sources can be readily eliminated. The display reported herein is the first step toward a real-time partial pixel architecture display in which large numbers of dynamic gratings are independently controlled by underlying silicon drive circuitry.

Real-time three-dimensional display based on the partial pixel architecture

We previously reported several static three-dimensional (3-D) display implementations of the partial pixel architecture [J. Opt. Soc. Am. A 12, 73 (1995)]. We report herein our f irst real-time 3-D display based on this architecture. The display is functionally equivalent to a real-time holographic stereogram. It is autostereoscopic and provides horizontal motion parallax. The display device is composed of a diffractive optical element (fabricated with standard photolithographic techniques) and a separate conventional liquidcrystal display. The display has been used to play back a precomputed animated 3-D scene at video frame rates using a standard VGA video output.

Partial pixels: a three-dimensional diffractive display architecture

We describe in detail the partial pixel architecture that permits the realization of three-dimensional (3-D) displays that are functionally equivalent to a real-time holographic stereogram. This architecture permits the simultaneous presentation of multiple stereoscopic images so that motion parallax is discernible in the resultant 3-D scene. The key innovation of the architecture is that each pixel is subdivided into partial pixels, which in turn can be implemented as individual diffraction gratings. We describe a static display that exhibits a 3-D image with one-dimensional motion parallax, thereby demonstrating key features of the architecture. A variety of partial pixel implementations are discussed that can operate at video frame rates. These include voltage-controlled liquid crystal gratings and binary optic gratings integrated with conventional liquid crystal amplitude modulators. In addition, we describe how the partial pixel architecture can be generalized for the implementation of full-color displays and displays having two-dimensional motion parallax.