CN101640761A - Vehicle-mounted digital television signal processing method - Google Patents

Abstract

The invention relates to a vehicle-mounted digital television signal processing method which respectively comprises steps of processing for video signals and the processing for audio signals. The processing for video signals comprises the following steps: (1) detecting moving regions: firstly, uniformly dividing all image frames into 36 blocks (6 lines and 6 rows), calculating the color attributeaverage value of each pixel point in each block one by one, and comparing the obtained color attribute average value with the color attribute average value of each pixel point of the corresponding block of the previous image frame, wherein if the difference value of the color attribute average values of the two blocks is smaller than the threshold value, the block is a static block, and if the difference value of the color attribute average values of the two blocks is not smaller than the threshold value, the block is a moving block, and all adjacent blocks of the block are moving blocks; (2)processing the static blocks in the image frames by average filtering; and (3) processing the moving blocks in the image frames by time-domain noise reduction. The vehicle-mounted digital television signal processing method processes the video signals by self-adapting noise reduction, thereby effectively reducing the noise, avoiding the loss of space details and improving the output effect of thevideo signals.

Description

Vehicle-mounted digital television signal processing method

(1) technical field

The present invention relates to a kind of vehicle-mounted digital television signal processing method.

(2) background technology

Mainly contain three kinds of Digital TV broadcasting standard for terrestrial in the world: the ISDB-T (Integrated Servic es Digital BroadcastingTerrestrial) (Integrated Services Digital Broadcasting) of the DVB-T (Digital VideoBroadcasting-Terrestrial) in Europe, the ATSC (Advanced Television SystemsCommittee) of the U.S. and Japan.DVB-T is a standard newer in the European DVB series standard (also has cable digital TV standard DVB-C in addition, and satellite digital TV standard DVB-S), also is the most complicated DVB transmission system.This standard is to approve in February, 1998.The core of DVB-T standard is a MPEG-2 digital video-audio compressed encoding, adopt Coded Orthogonal Frequency Division Multiplexing (COFDM) COFDM (CodedOrthogonal Frequency Division Multiplexing) modulation system, be applicable to the 8k carrier system of multi-transmitter on a large scale.DVB-T is that the transmission of high definition TV (HDTV) signal provides the payload code check greater than 20Mbps, supports the indoor fixedly reception of simple antenna; For the payload code check that provides greater than 5Mbps is provided standard definition television (SDTV) signal, and can under speed of a motor vehicle mobile condition, support to move reception; Has the single frequency network ability.ATSC is that the U.S. advanced television management consultant committee formally passes through ATSC Digital Television national standard September 15 nineteen ninety-five.ATSC system source encoding adopts MPEG-2 video compression and AC-3 audio compression; Chnnel coding adopts the VSB modulation, provides two kinds of patterns: terrestrial broadcasting pattern (8VSB) and High Data Rate pattern (16VSB).Along with the continuous development of multimedia transmission business, move the needs that receive in order to adapt to, be about to increase the mobile receiving mode of 2VSB now.Japan began to start autonomous digital television standard development project in 1996, on the basis of European COFDM technology, increase technology, form ISDB-T received terrestrial digital broadcasting transmission standard, in NEC communication technology review conference, pass through July nineteen ninety-five with independent intellectual property right.Calendar year 2001, this standard formally is accepted as a third place in the world digital television transfer international standard by ITU.Three kinds of standards are similar aspect source encoding, all adopt the MPEG-2 video compression, and the high-definition television image common format is 1920 * 1080,60/50 interlacing of per second, and maximum difference is the different of Channel Modulation and transmission means.Therefore, the incompatible receiver channel demodulation module that mainly is of three kinds of standard receivers.

China's terrestrial DTV transmission standard is issued (GB20600-2006) on August 18th, 2006, and (the GB terrestrial digital TV standard abbreviated DTMB-DigitalTerrestrial Multimedia Broadcasting. as from formal enforcement on August 1 in 2007.Be also referred to as DMB-TH in the time of early).A kind of main transmission mode in the GB adopts Domain Synchronous OFDM technology (TDS-OFDM), has independent intellectual property right, can support to move reception, digital TV in high resolution broadcasting and single frequency network preferably.Simultaneously, test shows is at spectrum utilization, and synchronizing speed supports that single antenna moves reception, and aspects such as indoor reception have also shown than DVB-T more performance.

Vehicle-mounted digital television receives the terrestrial wireless digital television signal by antenna, move the problem that is faced with dynamic multi-path and Doppler frequency shift when receiving, electromagnetic environment is abominable on automobile in addition, disturb strong, run into factors such as Changes in weather when adding running car, all can influence the signal output quality of mobile digital TV.

In the operating state of analog equipment on high speed (120KM/H) traveling automobile, and meet with external environment condition (as temperature, humidity, road quality etc.) after the variation, a large amount of research and analysises has been carried out in signal and the distribution of noise on frequency domain that digital television receiving apparatus receives, find that signal usually is distributed in lower frequency region, noise usually is distributed in high-frequency domain, and the details of image also is distributed in high-frequency domain, if carry out noise reduction process, simultaneously also with the important information of image also filtering with simple low-pass filtering method.

In addition, aspect the processing of audio signal, because stereo set and device, the frequency response curve of audio signal in the 20-20KHz scope is not a smooth straight line, equalizer can carry out careful adjustment to the frequency characteristic of whole system, obtains required frequency response curve.In fact parametric equalizer is made up of a kind of peak strip bandpass filter group, so the realization of the equalizer realization of peak filter just.General designing filter has two kinds of approach: first kind is to use the FIR structure, and second kind just is to use the IIR structure.But the two all can not be readjusted when operation, and to give the response that makes new advances, the FIR structure need recomputate all impulse response coefficients, thereby needs very big treating capacity; And IIR adopts is recursive structure, makes whole system have unsteadiness.

(3) summary of the invention

Technical problem to be solved by this invention provides a kind of vehicle-mounted digital television signal processing method that improves Voice ﹠ Video signal output quality.

A kind of vehicle-mounted digital television signal processing method comprises and respectively vision signal is handled and audio signal is handled, and wherein Video signal processing is comprised the steps:

(1) detect the moving region: vision signal is made up of the continuous images frame, earlier each picture frame is divided into 6 * 6 totally 36 pieces, the color attribute mean value of each pixel in the computing block one by one, the color attribute mean value with each pixel of previous image frame corresponding blocks compares then; If two color attribute mean value difference judges then that less than threshold values this piece is a static block; Otherwise judge that this piece is a moving mass, and all adjacent blocks of putting this piece are moving mass;

(2) adopt mean filter to handle to the static block in the picture frame;

(3) moving mass in the picture frame is adopted the time domain noise reduction process.

Further, described step (1) is specially:

A) finish initial setting up, the piece of preset recording static block is counted C=0;

B) (i, j) (i=0 wherein, 1,2,3,4,5 if the mark M of current block; J=0,1,2,3,4,5) be marked as motion or static, then do not deal with, directly change step f;

C) size of establishing the k picture frame is p * q pixel, calculates mean value S (i, j, k) (wherein=0,1,2,3,4,5 of each piece; J=0,1,2,3,4,5), that is:

$S(i,j,k)=\frac{\underset{m=1}{\overset{p/6}{\mathrm{\Σ}}}\underset{n=1}{\overset{q/6}{\mathrm{\Σ}}}g(i+m,j+n,k)}{\mathrm{pq}/36},$ Wherein g is the gray scale of current pixel point;

D) (k) (i, j k-l), if difference less than threshold value T1, during T1=25, is changeed step e, otherwise change step f with k-l frame corresponding blocks mean value S for i, j to compare S;

e)C＝C+1；

F) if current block relatively finishes, change step g over to, otherwise i=i+l changes steps d;

G) establish L=i*6+j+1, if C/L＞80%, (i j) is static block, otherwise is moving mass, and all adjacent blocks of putting current block are moving mass to put the mark M of current block;

H) detection of current block finishes, if i＜6, j＜6 change step c over to, otherwise finish the judgement of present frame.

Mean filter of the present invention is conventionally known to one of skill in the art, and mean filter is also referred to as linear filtering, and its main method that adopts is the field method of average.The basic principle of linear filtering is to replace each pixel value in the original image with average, promptly to pending current pixel point (x, y), select a template, this template is made up of some pixels of its neighbour, and the average of all pixels in seeking template is given current pixel point (x this average again, y), as handle at that point gray scale g of back image (x, y), i.e. g (x, y)=(x, y) m comprises current pixel in the total number of interior pixel in this template to 1/m ∑ f.

Further, the mean filter of described step (2) processing computing formula is as follows:

$\tilde{f}(i,j,k)=g(\·)\⊗\mathrm{\ω}(\·)=\underset{(m,n,l)\∈{\mathrm{\σ}}_{i,j,k}}{\mathrm{\Σ}}\mathrm{\ω}\left(l\right)g(i,j,k-1)---\left(1\right)$

In the formula:

$\mathrm{\&omega;}\left(1\right)=\left\{\begin{array}{c}1,({[g(i,j,k)-g(i,j,k-1)]}^2<T1)\\ 0,({[g(i,j,k)-g(i,j,k-1)]}^2\&GreaterEqual;T1)\end{array}\right\},$

$K(i,j,k)=1/\underset{l=0}{\overset{k}{\mathrm{\&Sigma;}}}\mathrm{\&omega;}\left(l\right)$ Be normalization coefficient.

" based on the adaptive time domain vedio noise reduction algorithm research of motion compensation " paper article that time domain noise reduction process of the present invention can be delivered at " semiconductor optoelectronic " with reference to Li Yan etc.Further, the time domain noise reduction process of described step (3) comprises that carrying out noise measuring judges the step of noise spot and noise spot is carried out the step of noise reduction process that described noise measuring comprises:

A, to arbitrary width of cloth digital picture f (x, y) vertical in level, set up 8 direction templates on 45 ° and the 135 ° of directions: { 1 ,-3 ,-1; 0,0,0; 1,2,1}, { 3 ,-2 ,-1;-1,0 ,-1;-1,0,1}, { 1,0,1;-2,1,2;-1,0,1}, { 0,1,2;-1,1 ,-1; 2 ,-1,0}, { 1,2,1; 0,0,0;-1,0 ,-1}, { 2,1,0; 1,0 ,-1; 0 ,-1 ,-2}, { 1,0 ,-1; 2,0,2; 1,0 ,-1}, { 0 ,-1 ,-2; 1,0 ,-1; 2,1,0};

B, each pixel in the image is calculated, obtain wherein maximum as the value of this point, and the represented direction of the template of this maximum correspondence is the direction of this pixel;

C, if | f (x, y)-f (x+i, y+j) |＞TH, TH=10 is for any i=0,1 ,-1; J=0,1 ,-1 all sets up, and then (x y) is noise spot to decidable.

Further, the computing formula of described noise reduction process is as follows:

$\tilde{f}(i,j,k)=g(\&CenterDot;)\&CircleTimes;\mathrm{\&omega;}(\&CenterDot;)=\underset{(m,n)\&Element;{\mathrm{\&sigma;}}_{i,j,k}}{\mathrm{\&Sigma;}}\mathrm{\&omega;}(m,n)g(i-m,j-n,k)---\left(2\right)$

In the formula:

$\mathrm{\&omega;}(m,n)=\frac{C(i,j)}{1+a\left(\max \right[T,{(g(i,j)-g(m,n))}^2\left]\right)}\exp \{-\frac{{(i-m)}^2+{(j-n)}^2}{2{\mathrm{\&sigma;}}^2}\}$

$C(i,j)=\frac{1}{\underset{(m,n)\&Element;{\mathrm{\&sigma;}}_{i,j,k}}{\mathrm{\&Sigma;}}\frac{\exp \{-\frac{{(i-m)}^2+{(j-n)}^2}{2{\mathrm{\&sigma;}}^2}}{1+a\left(\max \right[T,{(g(i,j)-g(m,n))}^2\left]\right)}}$

Further again, wherein the processing method to audio signal is:

(1) prototype function of employing peak filter:

$H\left(S\right)=\frac{S^2+S\frac{{\mathrm{\&Omega;}}_z}{Q_z}+{{\mathrm{\&Omega;}}_z}^2}{S^2+S\frac{{\mathrm{\&Omega;}}_p}{Q_p}+{{\mathrm{\&Omega;}}_p}^2}---\left(3\right)$

Qz, Qp represent the zero point of band pass filter and the quality factor of limit; Ω z, Ω p are the simulation angular frequency of zero point and limit, make Ω z=Ω p=Ω ₀, when Qp＞Qz, with V ₀=Qp/Qz, Q=Qp, Ω z=Ω p=Ω ₀Have in substitution (3) formula:

$H\left(S\right)=\frac{S^2+S\frac{V_0{\mathrm{\&Omega;}}_0}{Q}+{{\mathrm{\&Omega;}}_0}^2}{S^2+S\frac{{\mathrm{\&Omega;}}_0}{Q}+{{\mathrm{\&Omega;}}_0}^2}---\left(4\right)$

Formula (4) is carried out the z conversion, even:

$S=\frac{1-Z^{-1}}{1+Z^{-1}},$ $K={\mathrm{\&Omega;}}_0=\tan \left(\frac{{\mathrm{\&omega;}}_0}{2}\right)$

ω ₀Be the digital center angular frequency, can obtain formula (5) after the arrangement:

$H\left(z\right)=\frac{(1+V_{0}c+b)-2(1-b)z^{-1}+(1-V_{0}c+b)z^{-2}}{(1+c+b)-2(1-b)z^{-1}+(1-c+b)z^{-2}}---\left(5\right)$

B=K in the following formula ², C=K/Q is rewritten into following (6) formula with H (z):

$H\left(z\right)=\frac{a_0+a_1{z}^{-1}+a_2{z}^{-2}}{1+b_1{z}^{-1}+b_2{z}^{-2}}---\left(6\right)$

The coefficient that then promotes filter is as follows:

$a_0=\frac{1+V_0\frac{k}{Q}+k^2}{1+\frac{k}{Q}+k^2},$ $a_1=\frac{2(k^2-1)}{1+\frac{k}{Q}+k^2},$ $a_2=\frac{1-V_0\frac{k}{Q}+k^2}{1+\frac{k}{Q}+k^2},$

b ₁＝a ₁， $b_2=\frac{1-\frac{k}{Q}+k^2}{1+\frac{k}{Q}+k^2}$

The coefficient that in like manner subtracts filter is as follows:

$a_0=\frac{1+k{V}_{1}Q+k^2}{1+\mathrm{kQ}+k^2},$ $a_1=\frac{2(k^2-1)}{1+\mathrm{kQ}+k^2},$ $a_2=\frac{1-k{V}_{1}Q+k^2}{1+\mathrm{kQ}+k^2},$

$b_1=\frac{2(k^2-1)}{1+\mathrm{kQ}+k^2},$ $b_2=\frac{1-\mathrm{kQ}+k^2}{1+\mathrm{kQ}+k^2}.$

Beneficial effect of the present invention is:

(1) vision signal being carried out adaptive noise reduction handles; in effective noise reduction, avoided the loss of spatial detail again; guaranteed the filter effect of moving region; improved the output effect of vision signal; eliminated successfully that the television image card stops or the phenomenon of mosaic, obtained stable, distinct image effect.

(2) in the process to digital Audio Signal Processing, set up a cover centre frequency, gain and all adjustable digital parameter equalization algorithm of Q value, the user can adjust the parameter of parametric equalizer according to the hobby of oneself, to reach certain frequency range is given prominence to or desalinated, the acoustics in the automobile is optimized.

(4) embodiment

Below by embodiment the present invention is made preferably specific description, but protection scope of the present invention is not limited to this.

A kind of vehicle-mounted digital television signal processing method comprises and respectively vision signal is handled and audio signal is handled, and wherein Video signal processing is comprised the steps:

(1) detect the moving region: vision signal is made up of the continuous images frame, earlier each picture frame is divided into 6 * 6 totally 36 pieces, the color attribute mean value of each pixel in the computing block one by one, the color attribute mean value with each pixel of previous image frame corresponding blocks compares then; If two color attribute mean value difference judges then that less than threshold values this piece is a static block; Otherwise judge that this piece is a moving mass, and all adjacent blocks of putting this piece are moving mass;

(2) adopt mean filter to handle to the static block in the picture frame;

(3) moving mass in the picture frame is adopted the time domain noise reduction process.

Described step (1) is specially:

A) finish initial setting up, the piece of preset recording static block is counted C=0;

B) (i, j) (i=0 wherein, 1,2,3,4,5 if the mark M of current block; J=0,1,2,3,4,5) be marked as motion or static, then do not deal with, directly change step f;

C) size of establishing the k picture frame is p * q pixel, calculates mean value S (i, j, k) (i=0 wherein, 1,2,3,4,5 of each piece; J=0,1,2,3,4,5), that is:

$S(i,j,k)=\frac{\underset{m=1}{\overset{p/6}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{q/6}{\mathrm{\&Sigma;}}}g(i+m,j+n,k)}{\mathrm{pq}/36},$ Wherein g is the gray scale of current pixel point;

D) (k) (i, j k-l), if difference less than threshold value T1, during T1=25, is changeed step e, otherwise change step f with k-l frame corresponding blocks mean value S for i, j to compare S;

e)C＝C+1；

F) if current block relatively finishes, change step g over to, otherwise i=i+l changes steps d;

G) establish L=i*6+j+1, if C/L＞80%, (i j) is static block, otherwise is moving mass, and all adjacent blocks of putting current block are moving mass to put the mark M of current block;

H) detection of current block finishes, if i＜6, j＜6 change step c over to, otherwise finish the judgement of present frame.

It is as follows that the mean filter of described step (2) is handled computing formula:

$\tilde{f}(i,j,k)=g(\&CenterDot;)\&CircleTimes;\mathrm{\&omega;}(\&CenterDot;)=\underset{(m,n,l)\&Element;{\mathrm{\&sigma;}}_{i,j,k}}{\mathrm{\&Sigma;}}\mathrm{\&omega;}\left(l\right)g(i,j,k-1)---\left(1\right)$

In the formula:

$\mathrm{\&omega;}\left(1\right)=\left\{\begin{array}{c}1,({[g(i,j,k)-g(i,j,k-1)]}^2<T1)\\ 0,({[g(i,j,k)-g(i,j,k-1)]}^2\&GreaterEqual;T1)\end{array}\right\},$

$K(i,j,k)=1/\underset{l=0}{\overset{k}{\mathrm{\&Sigma;}}}\mathrm{\&omega;}\left(l\right)$ Be normalization coefficient.

The time domain noise reduction process of described step (3) comprises that carrying out noise measuring judges the step of noise spot and noise spot is carried out the step of noise reduction process that described noise measuring comprises:

A, to arbitrary width of cloth digital picture f (x, y) vertical in level, set up 8 direction templates on 45 ° and the 135 ° of directions: { 1 ,-3 ,-1; 0,0,0; 1,2,1}, { 3 ,-2 ,-1;-1,0 ,-1;-1,0,1}, { 1,0,1;-2,1,2;-1,0,1}, { 0,1,2;-1,1 ,-1; 2 ,-1,0}, { 1,2,1; 0,0,0;-1,0 ,-1}, { 2,1,0; 1,0 ,-1; 0 ,-1 ,-2}, { 1,0 ,-1; 2,0,2; 1,0 ,-1}, { 0 ,-1 ,-2; 1,0 ,-1; 2,1,0};

B, each pixel in the image is calculated, obtain wherein maximum as the value of this point, and the represented direction of the template of this maximum correspondence is the direction of this pixel;

C, if | f (x, y)-f (x+i, y+j) |＞TH, TH=10 is for any i=0,1 ,-1; J=0,1 ,-1 all sets up, and then (x y) is noise spot to decidable.

The computing formula of described noise reduction process is as follows:

$\tilde{f}(i,j,k)=g(\&CenterDot;)\&CircleTimes;\mathrm{\&omega;}(\&CenterDot;)=\underset{(m,n)\&Element;{\mathrm{\&sigma;}}_{i,j,k}}{\mathrm{\&Sigma;}}\mathrm{\&omega;}(m,n)g(i-m,j-n,k)---\left(2\right)$

In the formula:

$\mathrm{\&omega;}(m,n)=\frac{C(i,j)}{1+a\left(\max \right[T,{(g(i,j)-g(m,n))}^2\left]\right)}\exp \{-\frac{{(i-m)}^2+{(j-n)}^2}{2{\mathrm{\&sigma;}}^2}\}$

$C(i,j)=\frac{1}{\underset{(m,n)\&Element;{\mathrm{\&sigma;}}_{i,j,k}}{\mathrm{\&Sigma;}}\frac{\exp \{-\frac{{(i-m)}^2+{(j-n)}^2}{2{\mathrm{\&sigma;}}^2}}{1+a\left(\max \right[T,{(g(i,j)-g(m,n))}^2\left]\right)}}$

Wherein the processing method to audio signal is:

(1) prototype function of employing peak filter:

$H\left(S\right)=\frac{S^2+S\frac{{\mathrm{\&Omega;}}_z}{Q_z}+{{\mathrm{\&Omega;}}_z}^2}{S^2+S\frac{{\mathrm{\&Omega;}}_p}{Q_p}+{{\mathrm{\&Omega;}}_p}^2}---\left(3\right)$

Qz, Qp represent the zero point of band pass filter and the quality factor of limit; Ω z, Ω p are the simulation angular frequency of zero point and limit, make Ω z=Ω p=Ω ₀, when Qp＞Qz, with V ₀=Qp/Qz, Q=Qp, Ω z=Ω p=Ω ₀Have in substitution (3) formula:

$H\left(S\right)=\frac{S^2+S\frac{V_0{\mathrm{\&Omega;}}_0}{Q}+{{\mathrm{\&Omega;}}_0}^2}{S^2+S\frac{{\mathrm{\&Omega;}}_0}{Q}+{{\mathrm{\&Omega;}}_0}^2}---\left(4\right)$

Formula (4) is carried out the z conversion, even:

$S=\frac{1-Z^{-1}}{1+Z^{-1}},$ $K={\mathrm{\&Omega;}}_0=\tan \left(\frac{{\mathrm{\&omega;}}_0}{2}\right)$

ω ₀Be the digital center angular frequency, can obtain formula (5) after the arrangement:

$H\left(z\right)=\frac{(1+V_{0}c+b)-2(1-b)z^{-1}+(1-V_{0}c+b)z^{-2}}{(1+c+b)-2(1-b)z^{-1}+(1-c+b)z^{-2}}---\left(5\right)$

B=K in the following formula ², C=K/Q is rewritten into following (6) formula with H (z):

$H\left(z\right)=\frac{a_0+a_1{z}^{-1}+a_2{z}^{-2}}{1+b_1{z}^{-1}+b_2{z}^{-2}}---\left(6\right)$

The coefficient that then promotes filter is as follows:

$a_0=\frac{1+V_0\frac{k}{Q}+k^2}{1+\frac{k}{Q}+k^2},$ $a_1=\frac{2(k^2-1)}{1+\frac{k}{Q}+k^2},$ $a_2=\frac{1-V_0\frac{k}{Q}+k^2}{1+\frac{k}{Q}+k^2},$

b ₁＝a ₁， $b_2=\frac{1-\frac{k}{Q}+k^2}{1+\frac{k}{Q}+k^2}$

The coefficient that in like manner subtracts filter is as follows:

$a_0=\frac{1+k{V}_{1}Q+k^2}{1+\mathrm{kQ}+k^2},$ $a_1=\frac{2(k^2-1)}{1+\mathrm{kQ}+k^2},$ $a_2=\frac{1-k{V}_{1}Q+k^2}{1+\mathrm{kQ}+k^2},$

$b_1=\frac{2(k^2-1)}{1+\mathrm{kQ}+k^2},$ $b_2=\frac{1-\mathrm{kQ}+k^2}{1+\mathrm{kQ}+k^2}.$

Claims (6)

1, a kind of vehicle-mounted digital television signal processing method comprises and respectively vision signal is handled and audio signal is handled, and it is characterized in that: Video signal processing is comprised the steps:

(1) detect the moving region: vision signal is made up of the continuous images frame, earlier each picture frame is divided into 6 * 6 totally 36 pieces, the color attribute mean value of each pixel in the computing block one by one, the color attribute mean value with each pixel of previous image frame corresponding blocks compares then; If two color attribute mean value difference judges then that less than threshold values this piece is a static block; Otherwise judge that this piece is a moving mass, and all adjacent blocks of putting this piece are moving mass;

(2) adopt mean filter to handle to the static block in the picture frame;

(3) moving mass in the picture frame is adopted the time domain noise reduction process.

2, according to the vehicle-mounted digital television signal processing method of claim 1, it is characterized in that: described step (1) is specially:

A) finish initial setting up, the piece of preset recording static block is counted C=0;

B) (i, j) (i=0 wherein, 1,2,3,4,5 if the mark M of current block; J=0,1,2,3,4,5) be marked as motion or static, then do not deal with, directly change step f;

C) size of establishing the k picture frame is p * q pixel, calculates mean value S (i, j, k) (i=0 wherein, 1,2,3,4,5 of each piece; J=0,1,2,3,4,5), that is:

$S(i,j,k)=\frac{\underset{m=1}{\overset{p/6}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{q/6}{\mathrm{\&Sigma;}}}g(i+m,j+n,k)}{\mathrm{pq}/36},$ Wherein g is the gray scale of current pixel point;

D) (k) (i, j k-1), if difference less than threshold value T1, during T1=25, is changeed step e, otherwise change step f with k-1 frame corresponding blocks mean value S for i, j to compare S;

e)C＝C+1；

F) if current block relatively finishes, change step g over to, otherwise i=i+1 changes steps d;

G) establish L=i*6+j+1, if C/L＞80%, (i j) is static block, otherwise is moving mass, and all adjacent blocks of putting current block are moving mass to put the mark M of current block;

H) detection of current block finishes, if i＜6, j＜6 change step c over to, otherwise finish the judgement of present frame.

3, according to the vehicle-mounted digital television signal processing method of claim 1, it is characterized in that: it is as follows that the mean filter of described step (2) is handled computing formula:

$\tilde{f}(i,j,k)=g(\&CenterDot;)\&CircleTimes;\mathrm{\&omega;}(\&CenterDot;)=\underset{(m,n,l)\&Element;{\mathrm{\&sigma;}}_{i,j,k}}{\mathrm{\&Sigma;}}\mathrm{\&omega;}\left(l\right)g(i,j,k-1)---\left(1\right)$

In the formula:

$\mathrm{\&omega;}\left(1\right)=\left\{\begin{array}{cc}1,& ({[g(i,j,k)-g(i,j,k-1)]}^2<T1)\\ 0,& ({[g(i,j,k)-g(i,j,k-1)]}^2\&GreaterEqual;T1)\end{array}\right\},$

$K(i,j,k)=1/\underset{l=0}{\overset{k}{\mathrm{\&Sigma;}}}\mathrm{\&omega;}\left(l\right)$ Be normalization coefficient.

4, according to the vehicle-mounted digital television signal processing method of claim 1, it is characterized in that: the time domain noise reduction process of described step (3) comprises that carrying out noise measuring judges the step of noise spot and noise spot is carried out the step of noise reduction process that described noise measuring comprises:

A, to arbitrary width of cloth digital picture f (x, y) vertical in level, set up 8 direction templates on 45 ° and the 135 ° of directions: { 1 ,-3 ,-1; 0,0,0; 1,2,1}, { 3 ,-2 ,-1;-1,0 ,-1;-1,0,1}, { 1,0,1;-2,1,2;-1,0,1}, { 0,1,2;-1,1 ,-1; 2 ,-1,0}, { 1,2,1; 0,0,0;-1,0 ,-1}, { 2,1,0; 1,0 ,-1; 0 ,-1 ,-2}, { 1,0 ,-1; 2,0,2; 1,0 ,-1}, { 0 ,-1 ,-2; 1,0 ,-1; 2,1,0};

B, each pixel in the image is calculated, obtain wherein maximum as the value of this point, and the represented direction of the template of this maximum correspondence is the direction of this pixel;

C, if | f (x, y)-f (x+i, y+j) |＞TH, TH=10 is for any i=0,1 ,-1; J=0,1 ,-1 all sets up, and then (x y) is noise spot to decidable.

5, according to the vehicle-mounted digital television signal processing method of claim 4, it is characterized in that: the computing formula of described noise reduction process is as follows:

$\tilde{f}(i,j,k)=g(\&CenterDot;)\&CircleTimes;\mathrm{\&omega;}(\&CenterDot;)=\underset{(m,n)\&Element;{\mathrm{\&sigma;}}_{i,j,k}}{\mathrm{\&Sigma;}}\mathrm{\&omega;}(m,n)g(i-m,j-n,k)---\left(2\right)$

In the formula:

$\mathrm{\&omega;}(m,n)=\frac{C(i,j)}{1+a\left(\max \right[T,{(g(i,j)-g(m,n))}^2\left]\right)}\exp \{-\frac{{(i-m)}^2+{(j-n)}^2}{2{\mathrm{\&sigma;}}^2}\}$

$C(i,j)=\frac{1}{\underset{(m,n)\&Element;{\mathrm{\&sigma;}}_{i,j,k}}{\mathrm{\&Sigma;}}\frac{\exp \{-\frac{{(i-m)}^2+{(j-n)}^2}{2{\mathrm{\&sigma;}}^2}\}}{1+a\left(\max \right[T,{(g(i,j)-g(m,n))}^2\left]\right)}}$

6, according to the vehicle-mounted digital television signal processing method of claim 1, it is characterized in that: the processing method to audio signal is:

(1) prototype function of employing peak filter:

$H\left(S\right)=\frac{S^2+S\frac{{\mathrm{\&Omega;}}_z}{Q_z}+{{\mathrm{\&Omega;}}_z}^2}{S^2+S\frac{{\mathrm{\&Omega;}}_p}{Q_p}+{{\mathrm{\&Omega;}}_p}^2}---\left(3\right)$

Qz, Qp represent the zero point of band pass filter and the quality factor of limit; Ω z, Ω p are the simulation angular frequency of zero point and limit, make Ω z=Ω p=Ω ₀, when Qp＞Qz, with V ₀=Qp/Qz, Q=Qp, Ω z=Ω p=Ω ₀Have in substitution (3) formula:

$H\left(S\right)=\frac{S^2+S\frac{{V_0\mathrm{\&Omega;}}_0}{Q}+{{\mathrm{\&Omega;}}_0}^2}{S^2+S\frac{{\mathrm{\&Omega;}}_0}{Q}+{{\mathrm{\&Omega;}}_0}^2}---\left(4\right)$

Formula (4) is carried out the z conversion, even:

$S=\frac{1-Z^{-1}}{1+Z^{-1}},$ $K={\mathrm{\&Omega;}}_0=\tan \left(\frac{{\mathrm{\&omega;}}_0}{2}\right)$

ω ₀Be the digital center angular frequency, can obtain formula (5) after the arrangement:

$H\left(z\right)=\frac{(1+V_{0}c+b)-2(1-b)z^{-1}+(1-V_{0}c+b)z^{-2}}{(1+c+b)-2(1-b)z^{-1}+(1-c+b)z^{-2}}---\left(5\right)$

B=K in the following formula ², C=K/Q is rewritten into following (6) formula with H (z):

$H\left(z\right)=\frac{a_0+a_1{z}^{-1}+a_2{z}^{-2}}{1+b_1{z}^{-1}+b_2{z}^{-2}}---\left(6\right)$

The coefficient that then promotes filter is as follows:

$a_0=\frac{1+V_0\frac{k}{Q}+k^2}{1+\frac{k}{Q}+k^2},$ $a_1=\frac{2(k^2-1)}{1+\frac{k}{Q}+k^2},$ $a_2=\frac{1-V_0\frac{k}{Q}+k^2}{1+\frac{k}{Q}+k^2},$

b ₁＝a ₁， $b_2=\frac{1-\frac{k}{Q}+k^2}{1+\frac{k}{Q}+k^2}$

The coefficient that in like manner subtracts filter is as follows:

$a_0=\frac{1+k{V}_{1}Q+k^2}{1+\mathrm{kQ}+k^2},$ $a_1=\frac{2(k^2-1)}{1+\mathrm{kQ}+k^2},$ $a_2=\frac{1-k{V}_{1}Q+k^2}{1+\mathrm{kQ}+k^2},$

$b_1=\frac{2(k^2-1)}{1+\mathrm{kQ}+k^2},$ $b_2=\frac{1-\mathrm{kQ}+k^2}{1+\mathrm{kQ}+k^2}.$