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Noise Reduction

Smartec released outdoor camera with improved color rendering and noise reduction

New Smartec STC-3630 ULTIMATE outdoor camera provides round-the-clock video surveillance in outdoor conditions with low illumination. Due to Sony Super HAD II CCD, DSP processor, IR illumination and varifocal lens with AI, this outdoor camera generates a crisp image with 600 TVL resolution in Color and 700 TVL resolution in B/W modes. Due to the metal housing with IP66 rating and built-in heater, the camera can operate at temperatures ranging from -40 ° to +50 ° C. STC-3630 voltage supply is 12 V DC or 24 V AC.

1/3" camera features new Sony Super HAD II CCD with high sensitivity, improved dynamic range and noise reduction. This modern CCD provides outdoor camera operation at up to 0.15 lux in Color and up to 0.001 lux in B/W modes (IR illumination off). Due to DSP processor STC-3630 supports digital noise reduction (SSNR III) that improves image quality in low light conditions.

This outdoor model generates high-resolution images with 600/700 TVL resolution in Color and B/W modes respectively, ensuring the highest possible degree of image detail. To prevent sporadic switching between Color and B/W modes, outdoor camera allows installer to adjust delay time for Day/Night switching - from 5 to 60 seconds. Also, camera menu can be used for configuring camera switching between Day and Night modes.

In the absence of street lighting on the object the camera activates the built-in infrared illuminator with high light output, by adjusting power infrared illuminator, you can avoid the effect of "smearing" of the camera image when observing closely spaced street objects.

In case of lighting absence STC-3630 ULTIMATE activates 40 IR LEDs which provides up to 40 m of working range. When monitoring close objects installer can avoid "smearing" effect by adjusting the power of IR illumination. Smartec outdoor camera also allows installer to set the light level at which IR illumination will turn on automatically.

Due to the latest DSP processor, this outdoor camera supports digital noise reduction (SSNR III) that improves image quality in low light conditions. In addition, SSNR III function allows installer to save up to 70% of DVR disk space while recording video.

STC-3630 ULTIMATE features different functions that improve image quality. Thus, digital image stabilization (DIS) is used to eliminate image flicker, resulting from gusts of wind or other sources of vibrations. Due to the high light compensation (HLC) of the bright image areas, the adjacent areas of the image can be viewed more clearly. High dynamic range (SSDR) function enables installer to utilize STC-3630 camera on the applications with contrast lighting, suppressing extremely bright image areas and adding contrast to the image areas with a low light.

If necessary, STC-3630 allows installer to specify up to 8 motion detection areas with adjustable parameters (size, position, sensitivity). In addition, outdoor camera can configure up to 12 private masking zones on the image to block its view by the operator.

New outdoor camera allows installer to adjust camera lens and configure picture settings without full opening of the casing. Using camera hinged cover installer can get access to lens adjustment panel and on-screen menu navigation buttons. In addition, this outdoor model features compact size (83x82x166 mm) and is supplied with a feedthrough bracket.

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For more information, please, visit Smartec website or outdoor camera description

Noise Reduction $105.14 High Quality Content by WIKIPEDIA articles Noise reduction is the process of removing noise from a signal. Noise reduction techniques are conceptually very similar regardless of the signal being processed, however a priori knowledge of the characteristics of an expected signal can mean the implementations of these techniques vary greatly depending on the type of signal. All recording devices, both analogue or digital, have traits which make them susceptible to noise. Noise can be random or white noise with no coherence or coherent noise introduced by the devices mechanism or processing algorithms. In electronic recording devices, a major form of noise is hiss caused by random electrons that, heavily influenced by heat, stray from their designated path. These stray electrons influence the voltage of the output signal and thus create detectable noise. Author: Surhone, Lambert M./ Timpledon, Miriam T./ Marseken, Susan F. Binding Type: Paperback Number of Pages: 180 Publication Date: 2010/06/15 Language: English Dimensions: 5.98 x 9.01 x 0.41 inches

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Noise Reduction in Speech Processing $129 Suitable for graduate students and research engineers who work on noise reduction for speech and audio applications and want to understand the subtle mechanisms behind each approach, this book presents an overview of the noise reduction algorithms in the single-channel (one microphone) case.

Waves Z-Noise Native Noise Reduction Plug-In $375 The Waves Z-Noise Native Noise Reduction Plug-In raises the audio restoration bar. Waves originally set the standard for professional audio restoration software with their acclaimed X-Noise plug-in. Waves Z-Noise is a single-ended broadband noise reduction audio processor. It very effectively reduces noise while preserving the highest audio quality. Superficially, Z-Noise works like other broadband noise reduction processors that use a noise profile, or noise print, to differentiate valid signal from noise. Waves Z-Noise plug-in uses intelligent multilevel decision algorithms to maximize noise reduction with minimum unwanted artifacts. Plus, Z-Noise uses a more musical band split method for more natural results throughout the sound spectrum.The Z-Noise audio restoration software is ideal for removing additive noise such as tape hiss, vinyl surface damage, wind, air conditioner and ventilation system noise. Z-Noise offers several improvements, including:Z-Noise works on the complete frequency spectrum, thus high-frequency hiss and low-frequency rumble can be removed in the same pass, making it a truly broadband noise removal tool.Real-time operation allows you to adjust parameters and hear the results immediatelyExtract Profile ModeYou don't always have a section of pure noise from which to create a noise profile. Using the Extract Noise Profile feature, you can create a noise profile from a noise sample which is "contaminated" by program material you want to save.Adaptive Mode - You do not necessarily need to create a noise profile in order to reduce noise. In the Adaptive Mode, Z-Noise extracts a noise profile on-the-fly and reduces the noise even if the profile changes over time. Better transient treatmentWaves Z-Noise offers improved transient handling as well as enhanced transient processing options that allow for greater noise reduction with less transients smearing. The noise reduction software can detect and enhance transients prior to noise reduction processing, then de-enhance the transients after noise reduction, thus allowing for more aggressive noise reduction while preserving transients.Enhanced Noise profile adjustmentsIn both the normal and adaptive modes, Waves Z-Noise noise reduction software allows you to control the spectral nature of the noise profile. In this manner you can more precisely define what is a noise and what is program material.Knee control lets you adjust the angle of the knee to smooth or sharpen reduction dynamics. Brand new proprietary algorithmAccurate dynamic noise profilingBetter low frequency resolutionAdvanced transient preservation

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Noise Reduction in Speech Applications $159.95 Providing a comprehensive introduction to modern techniques for removing or reducing background noise from speech-related applications, this book focuses on system aspects, acoustic techniques, and digital algorithms and implementation.

Noise Reduction in Speech Processing (Hardcover) $259.33 Noise is everywhere and in most applications that are related to audio and speech, such as human-machine interfaces, hands-free communications, voice over IP (VoIP), hearing aids, teleconferencing/telepresence/telecollaboration systems, and so many others, the signal of interest (usually speech) that is picked up by a microphone is generally contaminated by noise. As a result, the microphone signal has to be cleaned up with digital signal processing tools before it is stored, analyzed, transmitted, or played out. This cleaning process is often called noise reduction and this topic has attracted a considerable amount of research and engineering attention for several decades. One of the objectives of this book is to present in a common framework an overview of the state of the art of noise reduction algorithms in the single-channel (one microphone) case. The focus is on the most useful approaches, i.e., filtering techniques (in different domains) and spectral enhancement methods. The other objective of Noise Reduction in Speech Processing is to derive all these well-known techniques in a rigorous way and prove many fundamental and intuitive results often taken for granted. This book is especially written for graduate students and research engineers who work on noise reduction for speech and audio applications and want to understand the subtle mechanisms behind each approach. Many new and interesting concepts are presented in this text that we hope the readers will find useful and inspiring.

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Noise Reduction by Wavelet Thresholding $95.51 This book discusses statistical applications of wavelet theory for use in signal and image processing. The emphasis is on smoothing by wavelet thresholding and extended methods. Wavelet thresholding is an example of nonlinear and nonparametric smoothing. The first part discusses theoretical and practical issues concerned with minimum risk thresholding and fast threshold estimation, using generalized cross validation. The extensions in later chapters consider possibilities to exploit three key properties of wavelets in statistics: sparsity, multiresolution, and locality. The author discusses original contributions to problems of correlated noise, scale dependent processing, Bayesian algorithms with geometrical priors (Markov random fields), nonequispaced data, and many other extensions. The point of view lies on the bridge between statistics, signal and image processing, and approximation theory, and the book is accessible for researchers from all of these fields. Most of the material has in mind applications in signal or image processing, and signals and images are used extensively in the illustrations. Nevertheless, the algorithms are quite general in the sense that they could also serve in other regression problems. The book also pays attention to fast algorithms, and Matlab code reproducing many of the illustrations is available for free. Maarten Jansen received a Ph.D. in applied mathematics from the Katholieke Universiteit Leuven, Belgium, in 2000 and currently he is a postdoctoral fellow with the Belgian Foundation for Scientific Research (FWO). He has been a visiting researcher at several institutes, including Stanford University, Bristol University, and Rice University. Author: Jansen, Maarten Series Title: Lecture Notes in Statistics Series Number: 161 Binding Type: Paperback Number of Pages: 224 Publication Date: 2001/03/30 Language: English Dimensions: 9.21 x 6.14 x 0.47 inches

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