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- Hui Li, B. S. Manjunath, Sanjit K. Mitra
- ICIP
- 1994

- Eduardo Abreu, Michael Lightstone, Sanjit K. Mitra, Kaoru Arakawa
- IEEE Trans. Image Processing
- 1996

A new framework for removing impulse noise from images is presented in which the nature of the filtering operation is conditioned on a state variable defined as the output of a classifier that operates on the differences between the input pixel and the remaining rank-ordered pixels in a sliding window. As part of this framework, several algorithms are… (More)

- Charles D. Creusere, Sanjit K. Mitra
- IEEE Trans. Signal Processing
- 1995

AbsCmct-This correspondence discusses a new method for designing the prototype filters necessary to implement M-band pseudo QMF banks. This method does not rely on the traditional nonlinear optimization used in past work but rather optimizes a single parameter on a convex error surface, consistently delivering the best equiripple filter possible while… (More)

- Hui Li, B. S. Manjunath, Sanjit K. Mitra
- IEEE Trans. Image Processing
- 1995

Image registration is concerned with the establishment of correspondence between images of the same scene. One challenging problem in this area is the registration of multispectral/multisensor images. In general, such images have different gray level characteristics, and simple techniques such as those based on area correlations cannot be applied directly.… (More)

- Zhihai He, Sanjit K. Mitra
- 2001

We present a new framework for rate–distortion ( – ) analysis, where the coding rate and distortion are considered as functions of which is the percentage of zeros among the quantized transform coefficients. In [1], we observe that, in transform coding of images and videos, the rate function ( ) is approximately linear. Based on this linear rate model, a… (More)

- Zhihai He, Sanjit K. Mitra
- IEEE Trans. Circuits Syst. Video Techn.
- 2002

We show that, in any typical transform coding systems, there is always a linear relationship between the coding bit rate and the percentage of zeros among the quantized transform coefficients, denoted by . Based on Shannon’s source coding theorem, a theoretical justification is provided for this linear source model. The physical meaning of the model… (More)

- Chin Chye Koh, J. Mukherjee, Sanjit K. Mitra
- IEEE Trans. Consumer Electronics
- 2003

Many consumer digital color cameras use a single light sensitive sensor and a color filter array (CFA) with each pixel element recording intensity information of one color component. The captured data is interpolated into a full color image, which is then compressed in many applications. Carrying out color interpolation before compression introduces… (More)

- Zhihai He, Sanjit K. Mitra
- IEEE Trans. Circuits Syst. Video Techn.
- 2001

In our previous work, we have developed a rate-distortion (R-D) modeling framework H.263 video coding by introducing the new concepts of characteristic rate curves and rate curve decomposition. In this paper, we further show it is a unified R-D analysis framework for all typical image/video transform coding systems, such as EZW, SPIHT and JPEG image coding;… (More)

- Jayanta Mukherjee, Sanjit K. Mitra
- IEEE Transactions on Image Processing
- 2008

This paper presents a new technique for color enhancement in the compressed domain. The proposed technique is simple but more effective than some of the existing techniques reported earlier. The novelty lies in this case in its treatment of the chromatic components, while previous techniques treated only the luminance component. The results of all previous… (More)

- Eduardo Abreu, Sanjit K. Mitra
- ICASSP
- 1995