KR0134269B1 - Method for calculating filter coefficient for ghost canceller - Google Patents

Abstract

The present invention relates to a filter coefficient calculation method of a ghost elimination device, and if the difference between the maximum value and the minimum value of the filter coefficient calculated by determining the position of the ghost and performing the LMS in the section where the ghost is present is smaller than the predetermined value, Compare the magnitudes of the maximum and minimum values. If the maximum value is large, the filter coefficient is 0 when the maximum value is less than 2 times the predetermined number and the value is smaller than 2 times the maximum value immediately after the maximum value. If the smallest and smallest value is less than twice the next smaller value, the filter coefficient is set to 0, thereby eliminating the incorrectly obtained filter coefficients, thereby improving the gosk removal function and preventing the deterioration of image quality due to the incorrectly calculated filter coefficients.

Description

Calculation method of ghost filter

1 is a schematic block diagram of a conventional ghost removal device.

FIG. 2 is a detailed block diagram of the filter unit and filter coefficient calculation unit of FIG.

3 is a flow chart showing the flow of the filter coefficient calculation method according to the present invention.

(A) of FIG. 4 is a waveform diagram showing the presence position of a long ghost as an example, and (b) is a waveform diagram showing a filter coefficient and an incorrectly obtained filter coefficient for removing the long ghost generated in (a).

* Explanation of symbols for main parts of the drawings

10: AD converter 20: reference signal extraction unit

30: filter coefficient calculation unit 40: filter unit

41: delay unit 42: FIR filter

43: IIR filter 50: DA converter

The present invention relates to a filter coefficient calculation method, and more particularly, to a filter coefficient calculation method of a ghost elimination device that can determine the suitability of the filter coefficient.

In general, a video signal from a broadcasting station is reflected by an obstacle such as a mountain or a building and is received by a receiving antenna, or a reflection dome is formed without impedance matching of a transmission path to form a multipath channel (MULTIPLE CHANNEL). As a result, the appearance of the reflected video signal other than the video signal on the monitor of the television is called Ghost.

FIG. 1 is a schematic block diagram of a conventional ghost elimination device, which includes an AD converter 10, a reference signal extractor 20, a filter coefficient calculator 30, a filter 40, and a DA converter 50. It is composed of

In the figure, the AD converter 10 converts the input video signal into a digital signal, and the reference signal extractor 20 converts the ghost removal reference signal inserted into a predetermined portion of the video signal converted into the digital signal. Extract. The filter coefficient calculator 30 calculates and transmits the filter coefficients using the ghost elimination reference signal stored in the input image signal through the pre-stored ghost elimination reference signal and the reference signal extractor 20, and then converts them into DA transforms. The unit 50 converts the filtered video signal back into an analog signal.

2 is a detailed block diagram of the filter coefficient calculation unit 30 and the filter unit 40. As can be seen from the figure, the filter unit 40 includes a flame retardant unit 41 which delays the video signal of the Winrae to remove the sun ghost, a FIR filter 42 which removes the near ghost and the sun ghost, and removes the long ghost. It consists of an IIR filter 43 and filters the input video signal using the filter coefficient transmitted from the filter coefficient calculation unit 30 and outputs it to the DA conversion unit 50.

Hereinafter, the principle of removing the ghost generated in the transmission path will be described in more detail with reference to FIGS. 1 and 2.

When the broadcast station inserts and sends a ghost removal reference signal to a predetermined portion of the video signal, the ghost removal apparatus inputs the video signal, switches the digital signal from the AD converter 20, and outputs the digital signal to the filter unit 40, and extracts the reference signal. By 20, the ghost removal reference signal inserted in the predetermined portion of the video signal converted into the digital signal is extracted.

The filter coefficient calculation unit 30 compares the ghost removal reference signal stored in advance with the ghost removal reference signal extracted from the input video signal through the reference signal extractor 20 to obtain a filter coefficient that can remove ghosts generated in the transmission path. Calculate and transmit to the FIR filter 42 and the IIR filter 43 in the filter unit 40, and the input image signal is filtered using the filter coefficients transmitted by the two filters (42, 43) in the transmission path The generated ghost is removed.

On the other hand, there are two methods for obtaining a filter coefficient having an inverse characteristic of channel characteristics: a sequential correction method and a batch correction method.

First, the batch correction method has a short convergence time and no problem of convergence, while the calculation amount is large and the error in the steady state is relatively large. For example, when using the FFT9FAST FOURIER TRANSFORM, which is one of the batch correction methods, it is different depending on the DSP (DIGITAL SIGNAL PROCESSOR) to be used. It is possible to calculate the filter coefficient for removal and send it to the filter section.

Secondly, the sequential correction method is small in computation and simple in formula, easy to implement and small in steady state, but has a convergence problem and takes a lot of time. For example, when using the LMS method, which is one of the axis correction methods, the filter coefficient is calculated for 1 second data input time, 2-4 seconds for a short time, and 10 seconds for a long time. Time is required.

If the LMS method is expressed by a formula, it is as follows.

From here,

In Equation (1), n [n] is a ghost elimination reference signal input to the ghost eliminating apparatus through a transmission path, and d [n] is an original ghost eliminating reference signal possessed by the ghost eliminating apparatus. And a0... aN-1 is a filter coefficient of the FIR filter whose number of filter coefficients is N1, and b1... bN2 is the filter coefficient of the IIR filter whose filter coefficient is N2. In addition, filter PG is the number of filter coefficients for removing pre-ghost from the FIR filter, and μ is a gain constant (GAIN CONSTANT) related to convergence safety and speed.

On the other hand, in the conventional ghost removal method, the correlation between the ghost removal reference signal inserted from the broadcasting station and the ghost removal reference signal of the ghost removal apparatus is obtained to find the channel characteristics and to determine the position of the long spot. After the determination, the LRS is performed only in the section where the long ghost exists without performing the LMS for all sections to calculate the filter coefficient.

Typically, the shape of a general long ghost as shown in FIG. If it exists.

As shown in (b) of FIG. 4, when the filter coefficients are correct (A filter coefficients, B filter coefficients), a plurality of local maxima and local minima are removed. If this exists, the largest value among the maximum values is relatively different from the second maximum value, and the smallest minimum value among the minimum values is relatively different from the second minimum value.

However, if the filter coefficient is incorrectly obtained (incorrectly obtained filter coefficient shown in (b) of FIG. 4), if the magnitude of the filter coefficient is small, there is no distinct maximum or minimum value and the shape of RANDOM NOISE is obtained. Have. Therefore, filtering an input video signal using an incorrectly obtained filter coefficient has a problem of degrading ghost removal performance and degrading image quality.

Accordingly, an object of the present invention is to provide a filter coefficient calculation method of a ghost removing device capable of removing a filter coefficient obtained incorrectly by determining suitability of the obtained filter coefficient.

In order to achieve the above object, the present invention provides a method for calculating a filter coefficient having a reverse characteristic of the channel characteristic for ghost removal after finding a channel characteristic between a transmission path and a receiving side, the maximum of the calculated filter coefficient. If the difference between the value and the minimum value is smaller than the predetermined value, the maximum value is compared with twice the predetermined value and the maximum value is smaller than twice the predetermined value and the maximum value is compared with two times the next larger value. If the value is small, the calculated filter coefficient is set to 0. If the minimum value is large in the comparing step, the minimum value is smaller than twice the predetermined value and the minimum value is compared with twice the predetermined value. Next, if the minimum value is small compared to twice the small value, the calculated filter coefficient is zero. An improved filter coefficient calculation method is provided.

Other objects and various advantages of the present invention will become more apparent from the preferred embodiments described below with reference to the accompanying drawings by those skilled in the art.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.

3 is a flow chart showing the flow of the improved filter coefficient calculation method of the present invention, which will be described in more detail with reference to FIGS. 1, 2, and 3 below.

First, the filter coefficient calculation unit 30 determines the position where the ghost is present by checking a correlation between the ghost removal reference signal extracted through the reference signal extraction unit 20 and the ghost removal reference signal stored in wheat.

Then, the LMS is performed only in the section where the ghost exists and the filter coefficient for removing the ghost is calculated. The difference between the maximum value and the minimum value of the calculated filter coefficients is calculated and compared with the set predetermined value (step 310), and if the difference is smaller than the set predetermined value, the magnitudes of the maximum value and the minimum value are compared (step 320). ).

As a result of the comparison of the step 320, if the maximum value is large, the maximum value is compared with twice the set predetermined value (step 330). If the maximum value is small, the value is two times the next largest value immediately after the maximum value. In comparison with (step 340), if the maximum value is small, the obtained filter coefficient is zero.

As a result of the comparison of the step 320, if the minimum value is large, the minimum value is compared with twice the predetermined value (step 360), and if the minimum value is small, the value is compared with twice the small value immediately after the minimum value. (Step 370), if the magnitude (absolute value) of the minimum value is small, the calculated filter coefficient is zero.

Therefore, according to the present invention, the filter coefficients obtained incorrectly, more specifically, the filter coefficients obtained for removing ghosts, are sufficiently small and the filter coefficients of which the maximum and minimum values of the filter coefficients are not clear are removed. .

As described above, by using the present invention, it is possible to enhance the ghost elimination performance by removing the erroneously calculated filter coefficients among the filter coefficients calculated for ghost elimination. There is an effect that can prevent the degradation of image quality caused by filtering.

Claims (1)

A method for calculating a channel coefficient between a transmission path and a receiving side and then calculating a filter coefficient having an inverse characteristic of the channel characteristic for ghost removal, wherein the difference between the maximum and minimum values of the calculated filter coefficient is greater than a predetermined value. Comparing the absolute value size between the maximum value and the minimum value if small; In the comparing step, when the maximum value is large, the maximum value is smaller than twice the predetermined value, and the maximum value is smaller than twice the predetermined value, and compared to twice the maximum value immediately after the maximum value. Setting the calculated filter coefficient to 0 if less than 0; If the minimum value is large in the comparing step, the minimum value is smaller than two times the predetermined value and the size of the minimum value is small compared to two times the maximum value immediately after the maximum value. An improved filter coefficient calculation method comprising the step of setting the calculated filter coefficient to zero.