主頁（http://m.by236.com）：在現代監控環境中使用紅外(IR)照明的好處【中英對照】(2) 在數字視頻監控應用中利用IR減少存儲需求 雖然使用紅外照明來提高圖像的質量和可用性廣受安防產業的認可，但它作為一個帶寬管理工具來使用可能會令人感到驚訝。由于存儲是運行一個安防系統導致的最大的開支之一，因而把IR來作為一個減少數字視頻應用中的存儲需求有效的工具，歡迎并要鼓勵這樣做將帶來驚喜。 作者：Ian Crosby 博世安防系統EMEA地區照明產品營銷經理 【英文原文】下一頁 Benefits of using infrared (IR) illumination in modern surveillance environments There is a simple rule which determines the effectiveness of any CCTV installation - without light there can be no picture. In this article, Ian Crosby (EMEA Product Marketing Manager - Illumination of Bosch Security Systems) looks into the effects of infrared (IR) illumination on bandwidth and how the use of IR lighting can contribute to reduced cost of storage in a modern video surveillance system. Managing bandwidth in low light conditions Whether analogue or digital (where encoding algorithms like H.264 encode analogue video for use with IP systems), virtually all CCTV cameras can capture good, useable images in bright, daytime conditions. However, it is how well your security system performs at night that determines its overall effectiveness, and since most crime takes place during the vulnerable hours of darkness, today's security systems need to be equipped for round-the-clock surveillance. It is precisely at night that most criminals will try to take advantage of weaknesses in surveillance systems The specifications of most modern security cameras state extremely low lux ratings - often in the range of 0.1 lux - seeming to suggest effective operation in very low light conditions. It is generally accepted however that without specialist CCTV illumination - be it visible white light or infrared - most cameras will only capture low quality, "noisy" images in dark, night-time conditions. Improving image quality and usability is one obvious benefit of specifying security illumination. However, another key benefit for CCTV users is only now coming to light. When light levels drop there is a significant increase in the bit rate of the encoded video stream from each camera in a network. This increased bit rate, if left unaddressed, will cause a substantial increase in the total storage costs of the system. Understanding automatic gain control (ACC) in night vision security cameras To understand why low light surveillance has such a higher bandwidth requirement and transmits video at a higher bit rate, we need to consider automatic gain control (AGC). AGC is camera technology, which increases signal strength in low light conditions. It works simply by amplifying the image; the effect of this amplification however is increased video signal and in turn increased image noise. Take a typical security installation: on-site surveillance cameras deliver good, useable images during the day but as darkness approaches the cameras' AGC function kicks in. The darker it gets the more AGC increases in magnitude and the images the cameras capture become grainy and "noisy". Eventually the image is completely obscured by "snow" and becomes practically useless. So why does "noisy" night-time surveillance video affect bit rate? Impact of video compression algorithms To understand why there is a rise in bit rate, it is important to have a basic understanding of how video compression algorithms work. The basic principle of compression is to eliminate all unessential information and reduce file size. All compression requires a compromise between image quality and file size. Higher compression ratios enable smaller file sizes but low quality images; lower compression ratios produce high quality images but need larger file sizes. Problems of low light conditions can be greatly reduced or eliminated with the proper surveillance camera technology With most installations, camera frame rate and resolution are adjusted to suit the applications needs; these parameters are generally specified up-front. While there is an obvious benefit to lowering frame rate and reducing resolution (lower bit rate) there is also a major disadvantage to doing this. Sacrificing frame rate and resolution results in low quality "choppy" surveillance video that can miss critical moments in a recorded event. Today's most popular video compression engines incorporate JPEG, MPEG or M-JPEG. Most recent is the new H.264 algorithm that uses approximately 30% less bandwidth than MPEG4 compression technology, which is itself 80% more efficient than M-JPEG. All however share common reduction principles; irrelevancy reduction, which removes sections of the video signal not noticeable by the human eye (like subtle colour changes) or redundancy reduction which removes duplicated information from either the same frame or between frames, large block areas of colour or stationary objects for example.
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