Cross sections and Rosenbluth separations from kaon electroproduction on protons up to Q2 = 2.35 (GeV/c)2

The kaon electroproduction reaction H(e, e ′K+)Λ was studied as a function of the four momentum transfer, Q2, for different values of the virtual photon polarization parameter. Electrons and kaons were detected in coincidence in two High Resolution Spectrometers (HRS) at Jefferson Lab. Data were taken at electron beam energies ranging from 3.4006 to 5.7544 GeV. The kaons were identified using combined time of flight information and two Aerogel Čerenkov detectors used for particle identification. For different values of Q2 ranging from 1.90 to 2.35 GeV/c2 the center of mass cross sections for the Λ hyperon were determined for 20 kinematics and the longitudinal, σ L, and transverse, σT, terms were separated using the Rosenbluth separation technique. ^ Comparisons between available models and data have been studied. The comparison supports the t-channel dominance behavior for kaon electroproduction. All models seem to underpredict the transverse cross section. An estimate of the kaon form factor has been explored by determining the sensitivity of the separated cross sections to variations of the kaon EM form factor. From comparison between models and data we can conclude that interpreting the data using the Regge model is quite sensitive to a particular choice for the EM form factors. The data from the E98-108 experiment extends the range of the available kaon electroproduction cross section data to an unexplored region of Q2 where no separations have ever been performed. ^

Color-based surface reflectance separation for scene illumination estimation and rendering

Given the importance of color processing in computer vision and computer graphics, estimating and rendering illumination spectral reflectance of image scenes is important to advance the capability of a large class of applications such as scene reconstruction, rendering, surface segmentation, object recognition, and reflectance estimation. Consequently, this dissertation proposes effective methods for reflection components separation and rendering in single scene images. Based on the dichromatic reflectance model, a novel decomposition technique, named the Mean-Shift Decomposition (MSD) method, is introduced to separate the specular from diffuse reflectance components. This technique provides a direct access to surface shape information through diffuse shading pixel isolation. More importantly, this process does not require any local color segmentation process, which differs from the traditional methods that operate by aggregating color information along each image plane. ^ Exploiting the merits of the MSD method, a scene illumination rendering technique is designed to estimate the relative contributing specular reflectance attributes of a scene image. The image feature subset targeted provides a direct access to the surface illumination information, while a newly introduced efficient rendering method reshapes the dynamic range distribution of the specular reflectance components over each image color channel. This image enhancement technique renders the scene illumination reflection effectively without altering the scene’s surface diffuse attributes contributing to realistic rendering effects. ^ As an ancillary contribution, an effective color constancy algorithm based on the dichromatic reflectance model was also developed. This algorithm selects image highlights in order to extract the prominent surface reflectance that reproduces the exact illumination chromaticity. This evaluation is presented using a novel voting scheme technique based on histogram analysis. ^ In each of the three main contributions, empirical evaluations were performed on synthetic and real-world image scenes taken from three different color image datasets. The experimental results show over 90% accuracy in illumination estimation contributing to near real world illumination rendering effects. ^