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- Niranjan Damera-Venkata, Thomas D. Kite, Wilson S. Geisler, Brian L. Evans, Alan C. Bovik
- IEEE Trans. Image Processing
- 2000

We model a degraded image as an original image that has been subject to linear frequency distortion and additive noise injection. Since the psychovisual effects of frequency distortion and noise injection are independent, we decouple these two sources of degradation and measure their effect on the human visual system. We develop a distortion measure (DM) of… (More)

- Thomas D. Kite, Niranjan Damera-Venkata, Brian L. Evans, Alan C. Bovik
- IEEE Trans. Image Processing
- 2000

Halftones and other binary images are difficult to process with causing several degradation. Degradation is greatly reduced if the halftone is inverse halftoned (converted to grayscale) before scaling, sharpening, rotating, or other processing. For error diffused halftones, we present (1) a fast inverse halftoning algorithm and (2) a new multiscale gradient… (More)

- Niranjan Damera-Venkata, Brian L. Evans
- IEEE Trans. Image Processing
- 2001

Grayscale digital image halftoning quantizes each pixel to one bit. In error diffusion halftoning, the quantization error at each pixel is filtered and fed back to the input in order to diffuse the quantization error among the neighboring grayscale pixels. Error diffusion introduces nonlinear distortion (directional artifacts), linear distortion… (More)

- Niranjan Damera-Venkata, Jonathan Yen, Vishal Monga, Brian L. Evans
- IEEE Transactions on Image Processing
- 2005

Error diffusion halftoning is a popular method of producing frequency modulated (FM) halftones for printing and display. FM halftoning fixes the dot size (e.g., to one pixel in conventional error diffusion) and varies the dot frequency according to the intensity of the original grayscale image. We generalize error diffusion to produce FM halftones with… (More)

- Niranjan Damera-Venkata, Brian L. Evans
- IEEE Trans. Image Processing
- 2001

Traditional error diffusion halftoning is a high quality method for producing binary images from digital grayscale images. Error diffusion shapes the quantization noise power into the high frequency regions where the human eye is the least sensitive. Error diffusion may be extended to color images by using error filters with matrix-valued coefficients to… (More)

- Niranjan Damera-Venkata, Nelson L. Chang
- 2007 IEEE Conference on Computer Vision and…
- 2007

We consider the problem of rendering high-resolution images on a display composed of multiple superimposed lower-resolution projectors. A theoretical analysis of this problem in the literature previously concluded that the multi-projector superimposition of low resolution projectors cannot produce high resolution images. In our recent work, we showed to the… (More)

- Niranjan Damera-Venkata, Nelson L. Chang
- ACM Trans. Graph.
- 2009

Supersampling is widely used by graphics hardware to render anti-aliased images. In conventional supersampling, multiple scene samples are computationally combined to produce a single screen pixel. We consider a novel imaging paradigm that we call <i>display supersampling</i>, where multiple display samples are physically combined via the superimposition of… (More)

| We present an inverse halftoning algorithm for error di used halftones. At each pixel, the algorithm applies a separable 7 7 FIR lter parameterized by the horizontal and vertical edge strengths computed from the local gradients. The algorithm requires entirely local operations, storage of 7 rows, and fewer than 300 arithmetic operations/pixel. The… (More)

This paper presents an extensible framework for designing analog filters that exhibit several desired behavioral properties after being realized in circuits. In the framework, we model the constrained nonlinear optimization problem as a sequential quadratic programming (SQP) problem. SQP requires real-valued constraints and objective functions that are… (More)

- Niranjan Damera-Venkata, José Bento, Eamonn O'Brien-Strain
- ACM Symposium on Document Engineering
- 2011

We present a new paradigm for automated document composition based on a generative, unified probabilistic document model (PDM) that models document composition. The model formally incorporates key design variables such as content pagination, relative arrangement possibilities for page elements and possible page edits. These design choices are modeled… (More)