Digital zoom camera with image sharpening and noise suppression

Weerasinghe, C.; Nilsson, Mats; Lichman, Serge; Kharitonenko, I.

doi:10.1109/tce.2004.1341679

Cited by 23 publications

(12 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As well known, CMOS image sensors suffer from high level noise and pixel cross-talk [2,14]. In order to achieve high quality images that are comparable to CCD image sensors, a new color processing chain, as shown in Figure 3, was proposed.…”

Section: Ptz Based Color Processingmentioning

confidence: 99%

“…The start addresses for accessing the CFA data are determined by the current pan and tilt values; whereas the address increment rate is determined by the current zoom value. Zoom values 1,2 and 4 are implemented in the camera [2,14].…”

Section: Color Interpolationmentioning

confidence: 99%

“…Under hardware constraints, a simple non-linear and hardware-friendly sharpening filter that proved its efficiency in [2,14] was implemented and employed in YUV color space. The filter has the following properties:…”

Section: Sharpness Enhancementmentioning

confidence: 99%

“…A line based anisotropic diffusion algorithm for noise reduction while preserving the edge sharpness was developed and implemented [2,14]. The correction weights for each pixel Y value are based on its immediate horizontal gradient.…”

Section: Noise Reductionmentioning

confidence: 99%

“…Figure 2 shows the architecture of proposed intelligent surveillance camera. The camera incorporates an automatic pan, tilt and zoom (PTZ) functionality implemented based upon [2,14] with the parameters decided upon captured activity within a specified region of interest (ROI). This provides more detailed visual information in zoomed modes while monitoring the full view at the same time.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A Prototype of Autonomous Intelligent Surveillance Cameras

Kharitonenko

Lichman

et al. 2006

2006 IEEE International Conference on Video and Signal Based Surveillance

View full text Add to dashboard Cite

This paper presents an architecture and an FPGAbased prototype of an autonomous intelligent video surveillance camera. The camera takes the advantage of high resolution of CMOS image sensors and enables instantly automatic pan, tilt and zoom adjustment based upon motion activity. It performs automated scene analysis and provides immediate response to suspicious events by optimizing camera capturing parameters. The video output of the camera can be optimized to any region of interest while the camera continues to monitor the entire scene. Field trials of the prototyped camera have verified the proposed architecture. Disciplines Physical Sciences and Mathematics

show abstract

Section: Ptz Based Color Processingmentioning

confidence: 99%

Section: Color Interpolationmentioning

confidence: 99%

Section: Sharpness Enhancementmentioning

confidence: 99%

Section: Noise Reductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Prototype of Autonomous Intelligent Surveillance Cameras

Kharitonenko

Lichman

et al. 2006

2006 IEEE International Conference on Video and Signal Based Surveillance

View full text Add to dashboard Cite

show abstract

Two‐dimensional adaptive Whittaker–Shannon Sinc‐based zooming

Ciulla,

Shabani,

Yahaya

2024

Applied Research

View full text Add to dashboard Cite

In this work, we introduce a novel image zooming methodology that transitions from a nonadaptive Sin‐based approach to an adaptive Sinc‐based zooming technique. The two techniques base their theoretical foundation on the Whittaker–Shannon interpolation formula and the Nyquist theorem. The evolution into adaptive Sinc‐based zoom is accomplished through the use of two novel concepts: (1) the pixel‐local scaled k‐space and (2) the k‐space filtering sigmoidal function. The pixel‐local scaled k‐space is the standardized and scaled k‐space magnitude of the image to zoom. The k‐space filtering sigmoidal function scales the pixel‐local scaled k‐space values into the numerical interval [0, 1]. Using these two novel concepts, the Whittaker–Shannon interpolation formula is elaborated and used to zoom images. Zooming is determined by the shape of the Sinc functions in the Whittaker–Shannon interpolation formula, which, in turn, depends on the combined effect of the pixel‐local scaled k‐space, the sampling rate, and the k‐space filtering sigmoidal function. The primary outcome of this research demonstrates that the Whittaker–Shannon interpolation formula can achieve successful zooms for values of the sampling rate significantly greater than the bandwidth. Conversely, when the sampling rate is much greater than the bandwidth, the nonadaptive technique fails to perform the zoom correctly. The conclusion is that the k‐space filtering sigmoidal function is identified as the crucial parameter in the adaptive Sinc‐based zoom technique. The implications of this research extend to Sinc‐based image zooming applications.

show abstract