DCT Domain Detail Image Enhancement for More Resolved Images

This paper develops a detail image signal enhancement that makes images perceived as being clearer and more resolved and so more effective for higher resolution displays. We observe that the local variant signal enhancement makes images more vivid, and the more revealed granular signals harmonically embedded on the local variant signals make images more resolved. Based on this observation, we develop a method that not only emphasizes the local variant signals by scaling up the frequency energy in accordance with human visual perception, but also strengthens the granular signals by embedding the alpha-rooting enhanced frequency components. The proposed energy scaling method emphasizes the detail signals in texture images and rarely boosts noisy signals in plain images. In addition, to avoid the local ringing artifact, the proposed method adjusts the enhancement direction to be parallel to the underlying image signal direction. It was verified through subjective and objective quality evaluations that the developed method makes images perceived as clearer and highly resolved.

DCT-Domain Detail Image Enhancement for More Resolved Images

This paper develops a detail image signal enhancement that makes images perceived as clearer and more resolved and so is more effective for higher resolution displays. We observe that the local variant signal enhancement makes images more vivid, and the more revealed granular signals harmonically embedded on the local variant signals make images more resolved. Based on this observation, we develop a method that not only emphasizes the local variant signals by scaling up the frequency energy in accordance with human visual perception, but also strengths up the granular signals by embedding the alpha-rooting enhanced frequency components. The proposed energy scaling method emphasizes the detail signals in texture images and rarely boosts noisy signals in plain images. In addition, to avoid the local ringing artifact, the proposed method adjusts the enhancement direction to be parallel to the underlying image signal direction. It was verified through the subjective and objective quality evaluations that the developed method makes images perceived as clearer and highly resolved.

An RGB-NIR Image Fusion Method for Improving Feature Matching

The quality of RGB images can be degraded by poor weather or lighting conditions. Thus, to make computer vision techniques work correctly, images need to be enhanced first. This paper proposes an RGB image enhancement method for improving feature matching which is a core step in most computer vision techniques. The proposed method decomposes near-infrared (NIR) image into fine detail, medium detail, and base images by using weighted least squares filters (WLSF) and boosts the medium detail image. Then, the fine and boosted medium detail images are combined, and the combined NIR detail image replaces the luminance detail image of an RGB image. Experiments demonstrates that the proposed method can effectively enhance RGB image; hence more stable image features are extracted. In addition, the method can minimize the loss of the useful visual (or optical) information of the original RGB image that can be used for other vision tasks.

Efficient onboard image motion compensation for orbital inclination and eccentricity of geostationary weather satellites

Image registration is important in geostationary weather satellites. Achieving consistent registration of the images with respect to the geographical locations on the Earth is here of interest. The consistency in the registration between the images is affected whenever the orbital inclination and eccentricity are not zero. The imaging payload has a two-axis scanning mirror to capture the Earth image. The above orbital effects together with scan mirror pointing direction are the factors that cause the misregistration. This paper presents an onboard algorithm that provides the scan compensation angles due to the above factors and achieves consistent registration. The compensation varies every second, which is the time taken for each scan. Hence it is preferred to have computations onboard than to have ground based bulk uplinks for the scan compensation. The paper presents an algorithm that is useful, say, when (i) the onboard computing capabilities are limited, (ii) the navigation accuracies are coarse and (iii) the image resampling is not preferred on the ground and the payload data are directly used for weather applications. The paper also discusses the tests that were carried on the onboard software in order to validate its performance in achieving the consistent registration before launch. This is done by using another independent software tool which is also described in detail. Image motion algorithm was invoked for a couple of days in INSAT 3DR. The atmospheric wind vector deduced directly from the satellite images is given at the end.

A novel multi-perspective imaging platform (M-PIP) for phenotyping soybean root crowns in the field increases throughput and separation ability of genotype root properties

BackgroundRoot crown phenotyping has linked root properties to shoot mass, nutrient uptake, and yield in the field, which increases the understanding of soil resource acquisition and presents opportunities for breeding. The original methods using manual measurements have been largely supplanted by image-based approaches. However, most image-based systems have been limited to one or two perspectives and rely on segmentation from grayscale images. An efficient high-throughput root crown phenotyping system is introduced that takes images from five perspectives simultaneously, constituting the Multi-Perspective Imaging Platform (M-PIP). A segmentation procedure using the Expectation-Maximization Gaussian Mixture Model (EM-GMM) algorithm was developed to distinguish plant root pixels from background pixels in color images and using hardware acceleration (CPU and GPU). Phenes were extracted using MatLab scripts. Placement of excavated root crowns for image acquisition was standardized and is ergonomic. The M-PIP was tested on 24 soybean [Glycine max (L.) Merr.] cultivars released between 1930 and 2005.ResultsRelative to previous reports of imaging throughput, this system provides greater throughput with sustained rates of 1.66 root crowns min-1. The EM-GMM segmentation algorithm with hardware acceleration was able to segment images in 10 s, faster than previous methods, and the output images were consistently better connected with less loss of fine detail. Image-based phenes had similar heritabilities as manual measures with the greatest effect sizes observed for Maximum Radius and Fine Radius Frequency. Correlations were also noted, especially among the manual Complexity score and phenes such as number of roots and Total Root Length. Averaging phenes across perspectives generally increased heritability, and no single perspective consistently performed better than others. Angle-based phenes, Fineness Index, Maximum Width, Holes, Solidity and Width-to-Depth Ratio were the most sensitive to perspective with decreased correlations among perspectives.ConclusionThe substantial heritabilities measured for many phenes suggest that they are potentially useful for breeding. Multiple perspectives together often produced the greatest heritabilities, and no single perspective consistently performed better than others. Thus, as illustrated here for soybean, multiple perspectives may be beneficial for root crown phenotyping systems. This system can contribute to breeding efforts that incorporate under-utilized root phenotypes to increase food security and sustainability.

Subsurface Zircons with Presumptive “Biogenic” Inclusions as Potentially Useful Proxies for Studying Precambrian Bygone Biospheres in Goa

This work was inspired by recent report by Bell et al., 2015 who studied potentially biogenic carbon preserved in a 4.1 billion-year-old Zircon and need to assess the potential of Zircons found in Goa. Zircons (ZrSiO4) are naturally occurring silicate minerals which show radioactivity and high ductility and contain traces of Thorium and Uranium useful in Uranium–Thorium /Thorium −230 dating techniques. Zircons can be found in igneous, metamorphic rocks, sedimentary deposits and occurs as a detrital minerals in river and beach sands. Previous reports show that the Zircons can occur in different shapes such as round, elongated and with surface characteristics (Gartner et al.,2013). U-Pb Zircon dating methods had been used to study the continental growth in the western Dharwar craton of southern India (Jayananda et al., 2015). The present study was aimed at detection of subsurface Zircons with biogenic inclusions and assess their use as proxies for studying bygone Precambrium biospheres in Goa. Deep tubewell drilled Cores (60 and 65 m deep from surface) in island of Tiswadi at Taleigao were analyzed by light microscopy, Phase contrast microscopy and SEM to detect and classify the Zircons. In rapid preliminary sampling, total 50 Zircons were identified and 98% indicated the presence of interesting inclusions. These could be bubbles or kerogens or unidentified biological material. Zircons were classified as elongated, slightly rounded with sharp edges and showed widespread variety of surface characteristics like fracturing, cracks, scratches, striations and impact pits which may occur during transport processes. It is suggested that Zircons with presumptive biogenic inclusions can be further studied using techniques such as Raman Spectroscopy, Carbon Isotopic Measurements, X-Ray Microscopy, Trace Element Measurement consistent with Bell et al., 2015. More exhaustive studies have been undertaken to create a detail image database of Zircons from various other local samples to pinpoint those specifically useful for advanced work based on image analysis of the presumptive bioinclusions. Further attempts would be made to develop specific harvesting techniques to select potentially useful Zircons. International collaborations would be sought for applications of advanced techniques to local Zircons. Such studies would shed light on nature of bygone Precambrian biospheres in Goa and help in understanding evolution of life and the impact of plate tectonics and cataclysmic events shaping life on this planet.

An Efficient Ear Recognition Method from Two-Dimensional Images

An efficient ear recognition method by weighted wavelet transformation and Bi-Directional principal component analysis was proposed. First, each ear image was decomposed into four sub-images by wavelet transformation ,the four sub-images were low frequency image , vertical detail image ,horizontal detail image and high frequency image .Then the low frequency image was decomposed into four sub-images, the four-images were weighted by different coefficients, then ,the four sub-images were reconstructed into a image .On this basis ,the feature was extraction by the BDPCA method ,and then we use the k-Nearest Neighbor Classification to recognition .Experimental results show that the method have high recognition rate and shorted training time.

New Enhancement Algorithm of Infrared Images Based on Dual Threshold of the Exponential Transform

Since the thermal imaging system detection ability and spatial resolution is lower than visible light CCD array,the definition of the infrared image is lower than that of the visible light image, which needs enhancement to improve image quality and for human vision. This paper proposes an enhancement algorithm of infrared images based on dual threshold of the exponential transform, firstly the original image can be processed by median filter to reduce noise,next separate the detail information of the 14-bit infrared image after noise reduction; then deal the detail image with the double threshold method based on the exponential transform,retaining or enhancing the detail information;when it comes to the base image,deal it with the gray linear mapping method, compressing its dynamic range.Finally the detail image and the base image are composed together after processing,getting 8-bit infrared image which can display and be processed on an ordinary display.

Image Processing Technology Research of On-Line Thread Processing

The paper introduced image processing technology based on image segmentation about on-line threads images, and describes in detail image processing technology from image preprocessing, image gmentation,and threaded parameter test. Threaded images of on-line processing parts obtained are introduced as the key technology, Target edge extraction process from the segmented image are also recounted. At last, this article shows a comparison between actual machining parameters of screw thread and the standard parameter , provides the criterion for error compensation.