Dror Kella

Measuring the modulation transfer function of image capture devices: what do the numbers really mean?

The modulation transfer function (MTF) is a fundamental tool for assessing the performance of imaging systems. It has been applied to a range of capture and output devices, including printers and even the media itself. In this paper, we consider the problem of measuring the MTF of image capture devices. We analyze the factors that limit the MTF of a capture device. Then, we examine three different approaches to this task based, respectively, on a slant-edge target, a sinewave target, and a grill pattern. We review the mathematical relationship between the three different methods, and discuss their comparative advantages and disadvantages. Finally, we present experimental results for MTF measurement with a number of different commercially available image capture devices that are specifically designed for capture of 2D reflection or transmission copy. These include camera-based systems, flat-bed scanners, and a drum scanner.

Laser print quality: practically continuous addressability

A novel method for resolution enhancement of Electro Photographic (EP) printers is presented. The proposed method is applicable for laser printers that have a partial-pixel exposure capability such as Pulse Width Modulation (PWM). By coupling partial exposure with anti-aliasing rendering, the proposed technology enables practically continuous addressability, namely, placement resolution. Using this technology we can show significant print quality improvement, such as the ability to render lines with arbitrary width and location. This would allow printing smooth line art at any angle with a relatively coarse pixel grid. The proposed method will thus provide better print quality compared to post process type resolution enhancement alternatives used today. The method has been tested theoretically using a Liquid EP (LEP) model, and experimentally confirmed.

Effect of image capture device on the accuracy of black-box printer models

In the process of electrophotograpic (EP) printing, the deposition of toner to the printer-addressable pixel is greatly influenced by the neighboring pixels of the digital halftone. To account for these effects, printer models can either be embedded in the halftoning algorithm, or used to predict the printed halftone image at the input to an algorithm that is used to assess print quality. Most recently,1 we developed a series of six new models to accurately account for local neighborhood effects and the influence of a 45 x 45 neighborhood of pixels on the central printer-addressable pixel. We refer to all these models as black-box models, since they are based solely on measuring what is on the printed page, and do not incorporate any information about the marking process itself. In this paper, we will compare black-box models developed with three different capture devices: an Epson Expression 10000XL (Epson America, Inc., Long Beach, CA, USA) flatbed scanner operated at 2400 dpi with an active field of view of 309.88 mm x 436.88 mm, a QEA PIAS-II (QEA, Inc., Billerica, MA, USA) camera with resolution 7663.4 dpi and a field of view of 2.4 mm x 3.2 mm, and Dr. CID, a 1:1 magnification 3.35 micron true resolution Dyson Relay lens-based 3 Mpixel USB CMOS imaging device2 with resolution 7946.8 dpi and a field of view of 4.91 mm 6.55 mm developed at Hewlett-Packard Laboratories { Bristol. Our target printer is an HP Indigo 5000 Digital Press (HP Indigo, Ness Ziona, Israel). In this paper, we will compare the accuracy of the black-box model predictions of print microstructure using models trained from images captured with these three devices.

Modeling large-area influence in digital halftoning for electrophotographic printers

Digital halftoning provides a mechanism for rendering continuous-tone images on devices such as printers. With electrophotography, the deposition of toner within the area of a given printer addressable pixel is strongly influenced by the halftone values of the immediately neighboring pixels. To account for these effects, it is necessary to embed a printer model in the halftoning algorithm. In our previous work, we used an efficient strategy to account for the impact of a 5x5 neighborhood of pixels on the central pixel absorptance. Now we examine the potential influence of a much larger neighborhood (45x45) of the digital halftone image on the measured value of a printed pixel at the center of that neighborhood. The experiment shows that the extended model yields a significant improvement in the accuracy of the prediction of the pixel values of the printed and measured halftone image.