Matrix optics is a general method to research and calculate geometric optical properties. Based on the principle of image formation for paraxial rays in geometrical optics, the ray tracing matrix properties of an illumination in Digital Light Processing (DLP) system are derived by ABCD matrix method for paraxial optics and optical elements is considered as thin-lens approximation, including fly-eye lens array, relay lens and TIR prisms. Through the theory analysis according to the transfer matrix, dual-face fly-eye lens array is measured as a function to change beam angle instead of beam characteristics, which is compared with single-face fly-eye lens. Consequently, the second surface of dual-face fly-eye lens can be seen as a field lens which can reduce the relay system diameter. In addition, it has been found that the TIR prisms generate magnification astigmatism and different angle magnification in meridian plane and sagittal plane, when the light beam transmits the TIR prisms, and could not be ignored in the DLP system design. Thus, a novel off-axis illumination system which employed a cylindrical lens is developed. The research indicates that the imagery quality of relay lens system is ideal, and the novel system can solve the difficult problems about astigmatism and angle magnification.
This paper presents a segment and spline synthesis optimization method (SSS method) for the freeform total-internal-reflection
(TIR) lens design. Before the optimization starts, a series of discrete control points are used to describe the TIR
lens profile. In order to realize initial optimization, the segment method is applied to optimize a linear-segmented TIR
lens. The final optimization is further achieved by the spline optimization method, after which the cubic-spline-modeling
TIR lens with the characteristic of low cost and easy fabrication could satisfy the target illumination requirements. The
detailed design principle and optimization process of the SSS method are both analyzed and compared in the paper.
Complementing each other, the synthesis of the segment and spline optimization method could realize the prescribed
design and greatly improve the design efficiency for designers. As an example, the specially designed polymethyl
methacrylate (PMMA) freeform TIR lens used for LED general lighting could demonstrate the effectiveness of this
method. The uniformity of the lens significantly increases from 67% to 88% after the segment and spline method,
respectively. High light output efficiency (LOE) of 99.3% is available within the target illumination area for the final
lens system. It is believed that the SSS method could be applied to design other freeform illumination optics.
Digital microscope has found wide application in the field of biology, medicine et al. A digital microscope differs from traditional optical microscope in that there is no need to observe the sample through an eyepiece directly, because the optical image is projected directly on the CCD/CMOS camera. However, because of the imaging difference between human eye and sensor, color image processing pipeline is needed for the digital microscope electronic eyepiece to get obtain fine image. The color image pipeline for digital microscope, including the procedures that convert the RAW image data captured by sensor into real color image, is of great concern to the quality of microscopic image. The color pipeline for digital microscope is different from digital still cameras and video cameras because of the specific requirements of microscopic image, which should have the characters of high dynamic range, keeping the same color with the objects observed and a variety of image post-processing. In this paper, a new color image processing pipeline is proposed to satisfy the requirements of digital microscope image. The algorithm of each step in the color image processing pipeline is designed and optimized with the purpose of getting high quality image and accommodating diverse user preferences. With the proposed pipeline implemented on the digital microscope platform, the output color images meet the various analysis requirements of images in the medicine and biology fields very well. The major steps of color imaging pipeline proposed include: black level adjustment, defect pixels removing, noise reduction, linearization, white balance, RGB color correction, tone scale correction and gamma correction.