If Progressive Scanning is So Good — How Bad is Interlace?

Thorpe, Laurence J.; Hanabusa, T.

doi:10.5594/j16791

Cited by 2 publications

(4 citation statements)

References 17 publications

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“…There is still considerable debate about the relative merits of sequential and interlaced scanning. Good discussions of this debate can be found in Thorpe &Hanabusa 1990. The difference between sequentially scanned film and interlaced signals from television cameras has significant practical consequences.…”

Section: Image Sourcesmentioning

confidence: 99%

“…Nevertheless, as an approximation, we may assume a perfect circular profile for the beam. This gives a Gaussian spatial frequency response (Thorpe & Hanabusa 1990) ie;…”

Section: 311mentioning

confidence: 99%

“…The second factor governing a tube's dynamic response is its lag, which depends on the rate at which charge is left behind following a single electron beam scan. The temporal (or dynamic) resolution of the sensor is thus given by (Thorpe & Hanabusa 1990)…”

Section: 311mentioning

confidence: 99%

“…This is done by simply stacking up the rows for the frequency domain constraints (equation 10) and for the time domain constraints. This gives a combined specification of; (35) where k is 1 over twice the Nyquist frequency for the (sampled) system. The gradient of the impulse response is given by;…”

Section: Time Domain Constraintsmentioning

confidence: 99%

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6 Television Standards Conversion

2012

Broadcast Engineer's Reference Book

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This thesis investigates the process of television standards conversion. That is converting a television signal originated in one standard for display in another standard. A typical example of this process is converting between European television, with 625 lines and 25 frames/second, and American television, with 525 lines and 30 frames/second. Although European/American interconversion is the best known type of standards conversion many other types are becoming necessary or desirable. These other standards conversion processes are between the burgeoning number of standards for high definition television, computer graphics as well as conventional television.The standards conversion process is, essentially, one of resampling a three dimensional sampled signal on a new sampling lattice. In one dimension the analogous process of sample rate changing is well understood. For standards conversion the theory of sample rate changing must be extended to three dimensions. Television standards conversion is much more difficult than sample rate changing an audio signal. This is partly because of the signal is 3 dimensional and partly because the sampling rates are orders of magnitude greater. The most significant problem of standards conversion, however, is the fact that television signals are undersampled spatially and, most significantly, temporally. Undersampling in television signals results in aliasing which confounds the assumptions underlying the theory of sample rate changing.At the start of this work the state of the art in television standards conversion involved interpolation of the signal using a 16 tap, 2 dimensional, finite impulse response filter. The filter coefficients were determined empirically to minimise the picture artifacts caused by the aliasing inherent in the signal. The first purpose of the work described here was to analyse the standards conversion process and develop objective methods of optimising the performance of the existing type of standards converters. It was likely that even optimised standards converters of this type would generate undesirable artifacts in their output pictures. I must also thank my colleagues and friends Dick Storey, Graham Thomas and Steve Dabner, with whom I spent much time discussing, designing and building the motion estimation system described in this thesis. Thanks also to Martin Weston for some of his thoughts and ideas on motion estimation and filter design.Many thanks to my wife Sally, who allowed me to write this thesis free from the all too friendly attention of our two young sons.The research described here was undertaken as a collaboration between Surrey University and the BBC Research Department. Many thanks to the British Broadcasting Corporation, for their support and for providing the facilities which enabled me to undertake this work.Thanks to Philips Research Laboratories and, in particular, Dave Parker and MikeHulyer with whom I worked on motion compensated display field rate upconversion.Thanks to the Vistek company for providing the experimental m...

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Section: Image Sourcesmentioning

confidence: 99%

“…Nevertheless, as an approximation, we may assume a perfect circular profile for the beam. This gives a Gaussian spatial frequency response (Thorpe & Hanabusa 1990) ie;…”

Section: 311mentioning

confidence: 99%

Section: 311mentioning

confidence: 99%

Section: Time Domain Constraintsmentioning

confidence: 99%

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6 Television Standards Conversion

2012

Broadcast Engineer's Reference Book

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Statistical characteristics of granular camera noise

Cortelazzo

Mian

Parolari

1994

IEEE Trans. Circuits Syst. Video Technol.

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Granular camera noise is per se objectionable in high-quality TV and it is a source of bothersome visual artifacts with digitally coded video sequences. The first and second-order statistical characteristics of this noise are investigated in this work. The results quantify intuitively expected notions, such as the relative unimportance of chrominance noise with respect to the luminance noise and the spatially colored nature of the noise. Noise reduction techniques can use, as general guidance rules, the indications of the presented analysis.

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If Progressive Scanning is So Good — How Bad is Interlace?

Cited by 2 publications

References 17 publications

6 Television Standards Conversion

6 Television Standards Conversion

Statistical characteristics of granular camera noise

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