The standard H.264 ip camera main objectives are: and other existing video coding standard compared to the same bandwidth to provide more excellent image quality. H.264 and previous international standards such as H.263 and MPEG-4 compared to in order to achieve efficient compression, full use of redundancy, redundancy and statistical redundancy visual physiology. 1, statistical redundancy: Redundant spectrum (referring to the correlation between color components), spatial redundancy, as well as time redundancy. This is a video compression is different from the fundamental point still images, video compression major use of time redundancy to achieve large compression ratio. 2, visual physiological redundancy Redundancy is due to the visual physiology of human visual system (HVS) characteristics caused by the human eye such as high-frequency components of the color components of the luminance component is not sensitive to high-frequency components, the image frequency (ie the details) is not sensitive to noise at and so on. For these redundant, video compression algorithms use a different method be used, but the main consideration is focused on the spatial redundancy and temporal redundancy. H.264 ip camera also mixed (hybrid) structure, namely, spatial redundancy and temporal redundancy, respectively, for processing. Of spatial redundancy, and quantitative standards to eliminate by changing the purpose of this frame is called I-frame coding; and time redundancy is through inter prediction, motion estimation and compensation is to remove, so called P-frame coding frame or B frame. The difference is that with the previous standards, H.264 I-frame encoding, the use of intra prediction, and then encode the prediction error. This full advantage of the spatial correlation to improve the coding efficiency. 16x16 intra prediction for H.264 macroblock as the basic unit. First, the encoder and the current macro block neighboring pixels, the same frame as a reference, resulting in the current macro block of the predicted value, then the prediction residual transform and quantization, and then transform and quantification of the results do entropy coding. Entropy coding the results of a stream can be formed. Since the decoder side can be the reference data are quantified through the inverse transform and reconstruction after the anti-image, so in order to make the same codec, the encoder used to predict the reference data and the decoder on the same side, but also through the inverse transform and inverse quantization reconstruction image.