Novel vectorization method for high resolution images

Designing an optical aerial imaging system with high resolution and large fields of view (FoV) is a longstanding problem in remote sensing, astronomical observation, and geological exploration. In this paper, we propose a light field-guided optical synthetic aperture imaging system on master-slave unmanned aerial vehicles (UAVs). This system consists of single-master UAV and multiple-slave UAVs to capture cross-scale multiview aerial images to stitch an aerial image and even a video with high resolution and large FoV. However, relative poses of UAVs change dynamically during the flight, which causes the inaccuracy of large-FoV image stitching. To address this problem, we convert image stitching as a novel-view synthesis problem on a large-FoV light field. Under this insight, we construct a 5D light field to cover FoVs of all slave UAVs via Gaussian splatting technique. Then we exploit a light field-guided synthetic aperture imaging scheme to generate the high-resolution image. Additionally, this scheme can be extended for large-FoV video generation. Experimental results on real-world scenes show that the proposed imaging system is capable of generating the accurate, large-FoV, high-resolution image sequences. Hence, we believe that this system has great potential in large-FoV high-resolution aerial imaging.

Lower resolution is the main shortcoming for geometrical model. Mesh smoothing is a basic method for turning a coarse and lower resolution model into a smooth one. The paper proposed a mesh smoothing method for parameterized geometrical body model based on the Loop subdivision. A smooth surface can be expressed with a lot of subdivision control meshes that has higher resolution with mesh subdivision rules. It can effectively avoid the shortcomings of coarser and lower resolution of parameterized geometrical model. Experiment shows that the method is meaningful for the geometrical body model based on parameterized modeling method and can produce multi-curvature mesh surface. It is simple, efficient and can preserve the features of the original model.

To meet various transmission and storage constraints, it is desirable that a compression algorithm allows a range of compression ratios. In this paper we analyze the JPEG compression algorithm, the international standard for compressing continuous tone images, and show how higher compression ratios can be achieved with minimal loss in image quality. We compare three methods to achieve variable compression with JPEG. Through a comprehensive analysis using 8 standard monochrome images from the USC database, we propose a method that offers substantial visual quality advantages for high compression ratios. The comparisons have been made by using an objective distortion measure which corresponds well to subjective assessments of visual quality. The paper provides detailed motivation for the algorithms, and suggests the choice of parameters to obtain variable compression with minimal loss in visual quality. >

A Dual Image Sensor Approach for Automated, High Resolution, Region-of-Interest Imaging in a 96-Well Plate

Multiplexed Superresolution CRISPR Imaging of Chromatin in Living Cells

High-resolution imaging using Hadamard Encoding

Imaging of the cervical spine in functional positions has so far been limited to conventional X-ray examinations or the scarcely available open magnetic resonance imaging (MRI). An MRI compatible positioning device allows MRI examinations in various positions and even in motion. In combination with high-resolution T2-weighted MRI it allows detailed functional imaging of the cervical spine and nerve roots. To evaluate the utility of this method a population of patients from a clinical study was examined 5 years after anterior cervical discectomy and fusion (ACDF). A total of 32 patients (median age 51.5 years, 15 female, 17 male) were examined after a median interval of 64.3 months from ACDF including 16 patients with a titanium cage and 16 with autologous bone graft. The prototype of an MR compatible positioning device (NeuroSwing) was used for MRI of the cervical spine in functional positions on a 1.5 T MRI unit (Siemens Avanto). A real-time true fast imaging with steady-state precession (FISP) sequence [6 mm, TR 704, TE 1.3 ms, matrix 256 x 207, field of view (FoV) 22 cm] was used for monitoring of flexion up to 45° and extension up to 40° or until patient discomfort. A sagittal T2 sampling perfection with application optimized contrast using different flip angle evolution sequence (SPACE sequence, 0.9 mm isotropic voxels, TR 1770, TE 186 ms, matrix 320 x 318, FoV 28 cm) and an axial true FISP sequence (3 mm slices, TR 194, TE 1.9 ms, matrix 256 x 256, FoV 22 cm) were used for imaging in the end positions. Using the motorized positioning device and a real-time true FISP sequence, imaging of the cervical spine in flexion and extension motion was possible in a quality suitable to observe changes in the alignment of vertebral bodies, the width of the spinal canal and the spinal cord itself. The 3D T2-weighted SPACE sequence yielded high quality and resolution images in the maximum flexion and extension positions. Compared to primary axial T2 true FISP slices, axial reconstructions of the T2 SPACE sequence were found to be clearly less affected by metal artifacts with the additional benefit of multiplanar and transforaminal reconstructions. The combination of a mechanical positioning device and a high-resolution 3D T2-weighted sequence (SPACE) on a conventional 1.5 T MRI allows kinematic imaging of the cervical spine as well as high-resolution imaging in the end positions, even in the presence of metal implants. In this proof of concept study a good visualization of narrowing of the spinal canal in functional positions could be achieved, showing the potential of MRI in functional positions for clinical and research applications.

Image super-resolution is of great interest in medical imaging field. However, different from natural images studied in computer vision field, the low-resolution (LR) medical imaging data is often a stack of high-resolution (HR) 2D slices with large slice thickness. Consequently, the goal of super-resolution for medical imaging data is to reconstruct the missing slice(s) between any two consecutive slices. Since some modalities (e.g., T1-weighted MR image) are often acquired with high-resolution (HR) image, it is intuitive to harness the prior self-similarity information in the HR image for guiding the super-resolution of LR image (e.g., T2-weighted MR image). The conventional way is to find the profile of patchwise self-similarity in the HR image and then use it to reconstruct the missing information at the same location of LR image. However, the local morphological patterns could vary significantly across the LR and HR images, due to the use of different imaging protocols. Therefore, such direct (un-supervised) adaption of self-similarity profile from HR image is often not effective in revealing the actual information in the LR image. To this end, we propose to employ the existing image information in the LR image to supervise the estimation of self-similarity profile by requiring it not only being optimal in representing patches in the HR image, but also producing less reconstruction errors for the existing image information in the LR image. Moreover, to make the anatomical structures spatially consistent in the reconstructed image, we simultaneously estimate the self-similarity profiles for a stack of patches across consecutive slices by solving a group sparse patch representation problem. We have evaluated our proposed super-resolution method on both simulated brain MR images and real patient images with multiple sclerosis lesion, achieving promising results with more anatomical details and sharpness.

The problem of energy conservation in wireless image sensor networks is addressed, and a fast zonal discrete consine transform (DCT) design which aims to decrease the complexity of JPEG baseline compression is presented. Energy consumption measurements have been made on a real wireless camera node in order to evaluate the amount of energy which can be saved during the image compression process without loss of visual quality. Although the gain depends on the compression rate, such a DCT design is a simple and effective way to prolong the lifetime of the camera nodes, and thereby the network lifetime.

In this paper, an innovative method of HEVC video pre-processing is proposed. The method applies a simple linear iterative clustering (SLIC), which adapts a k-means clustering to group pixels into perceptually meaningful atomic regions of superpixels. By calculating the average of weighted average of luminance differences around each pixel in the superpixel, a suitable parameter of Gaussian filter for the superpixel is determined. Experimental results show that bit rate can be reduced up to 29% without loss in visual quality.

Texture mapping is a common operation to increase the realism of three-dimensional meshes at low cost. We propose a new texture optimization algorithm based on the reduction of the physical space allotted to the texture image. Our algorithm optimizes the use of texture space by computing a warping function for the image and new texture coordinates. Neither the mesh geometry nor its connectivity are modified by the optimization. Our method uniformly distributes frequency content of the image in the spatial domain. In other words, the image is stretched in high frequency areas, whereas low frequency regions are shrunk. We also take into account distortions introduced by the mapping onto the model geometry in this process. The resulting image can be resampled at lower rate while preserving its original details. The unwarping is performed by the texture mapping function. Hence, the space-optimized texture is stored as-is in texture memory and is fully supported by current graphics hardware. We present several examples showing that our method significantly decreases texture memory usage without noticeable loss in visual quality.

Over the last few decades, the Chilean Government has constantly promoted the construction of private highways in order to increase the effectiveness in terms of transportation of goods and people all along the country. In this way, heavy road infrastructures, landscape fragmentation, loss of endangered animals’ habitat, loss of visual quality, and a decrease of biodiversity patches have emerged. Despite this, some greenery – native and introduced flora/fauna, natural elements, colors, lines, patterns, among others- can be partly seen in certain areas of Chilean highways. In particular, this paper focuses on the main route connecting Puerto Montt and Pargua cities in Los Lagos region.The objectives of this qualitative research are threefold. Firstly, to measure main Landscape attributes and Visual scale characteristics through a fieldwork by the roadside of Pargua highway (Alto Bonito Area) using a scale of attributes adapted from Tveit et al. (2007). Secondly, to measure the type of vegetation through an environmental inventory (phytosociological analysis). Thirdly, to measure the degree of management of the highway considering its maintenance and human intervention.Wilderness and Naturalness are scarcely observed on the roadside due to a concentrated presence of human interventions such as landfills and overpasses. The visual scale is checked in fieldwork from several scopes. On the southeast side of the road, Las Canchas Area is covered by high trees, houses, and industries which hinder the view of the natural surrounding landscape. On the right side of the road, it presents a clear skyline of Calbuco and Osorno volcanoes. Finally, any management of high quality of the visual scenery of this type of landscape from the route concessionaire is is randomly done. However, the vegetation surface itself has been working out a way to protect the land from erosion and desertification.

Color bit-depth is an important attribute to image quality. However, the precision in various image capture devices limits the color bit-depth and introduces loss in visual quality. Expanding the color bit-depth is an important image enhancement issue. A good bit-depth expansion system manipulates low color bit-depth image for best visual quality as displayed on high color bit-depth monitors. However, in most color bit-depth expansion algorithms, severe contouring effect is observed in smooth gradient area which degrades the visual quality. In this paper, a novel approach is proposed. By considering the distance from contour edges, fine gradient value are applied to fill the contour gaps to achieve gradual transaction.

Patient motion is inevitable in SPECT and PET due to the lengthy period of time patients are imaged and patient motion can degrade diagnostic accuracy. The goal of our studies is to perfect a methodology for tracking and correcting patient motion when it occurs. In this paper we report on enhancements to the calibration, camera stability, accuracy of motion tracking, and temporal synchronization of a low-cost visual tracking system (VTS) we are developing. The purpose of the VTS is to track the motion of retro-reflective markers on stretchy bands wrapped about the chest and abdomen of patients. We have improved the accuracy of 3D spatial calibration by using a MATLAB optical camera calibration package with a planar calibration pattern. This allowed us to determine the intrinsic and extrinsic parameters for stereo-imaging with our CCD cameras. Locations in the VTS coordinate system are transformed to the SPECT coordinate system by a VTS/SPECT mapping using a phantom of 7 retro-reflective spheres each filled with a drop of Tc(99m). We switched from pan, tilt and zoom (PTZ) network cameras to fixed network cameras to reduce the amount of camera drift. The improved stability was verified by tracking the positions of fixed retro-reflective markers on a wall. The ability of our VTS to track movement, on average, with sub-millimeter and sub-degree accuracy was established with the 7-sphere phantom for 1 cm vertical and axial steps as well as for an arbitrary rotation and translation. The difference in the time of optical image acquisition as decoded from the image headers relative to synchronization signals sent to the SPECT system was used to establish temporal synchrony between optical and list-mode SPECT acquisition. Two experiments showed better than 100 ms agreement between VTS and SPECT observed motion for three axial translations. We were able to track 3 reflective markers on an anthropomorphic phantom with a precision that allowed us to correct motion such that no loss in visual quality was noted in motion corrected slices relative to motion free slices.

Indian Remote Sensing (IRS) Resourcesat satellites have AWiFS, LISS-III, LISS-IV sensors of 56m, 23.2m, 5.8m spatial resolutions respectively and of having identical spectral and temporal (simultaneous acquisition) resolutions but they are different in spatial and radiometric resolutions. In this work, we are trying to create high resolution (HR) image from coarser resolution AWiFS image called as emulated LISS-III like HR image. It will have HR (original LISS-III) image characteristics and minimal Mean Squared Error (MSE), ideally zero difference with LISS-III image as refernce, which inturn processed for identical spatial resolution of LISS - III. Ground sampling distance (GSD) of AWiFS is equivalent to 2.4 pixels of LISS-III. Radiance values are compared for normalization purpose, after weighted averaging of LISS-III to create AWiFS equivalent spatial resolution. Spatial resolution can be enhanced by improving the spatial sampling density of the signal. Nyquist-Shannon sampling theorem directs the sampling rate for exact reconstruction of the signal. The Resourcesat images are pre-processed to match this condition. Papoulis-Gerchberg algorithm is suitably improved for constructing the HR image from AWiFS. The results are compared with the classical interpolation techniques such as nearest neighbor, bilinear, spline, cubic convolution Papoulis-Gerchberg and modified Papoulis-Gerchberg [1].