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Performance Comparison of Ringing Artifact for the Resized Images Using Gaussian Filter and OR Filter

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Performance Comparison of Ringing Artifact for the Resized Images Using Gaussian Filter and OR Filter ISSN: 2278 – 909X International Journal of Advanced Research in Electronics and Communication Engineering (IJARECE) Volume 2, Issue 3, March 2013 Performance Comparison of Ringing Artifact for the Resized images Using Gaussian Filter and OR Filter Jinu Mathew, Shanty Chacko, Neethu Kuriakose developed for image sizing. Simple method for image resizing Abstract — This paper compares the performances of two approaches which are used to reduce the ringing artifact of the digital image. The first method uses an OR filter for the is the downsizing and upsizing of the image. Image identification of blocks with ringing artifact. There are two OR downsizing can be done by truncating zeros from the high filters which have been designed to reduce ripples and overshoot of image. An OR filter is applied to these blocks in frequency side and upsizing can be done by padding so that DCT domain to reduce the ringing artifact. Generating mask ringing artifact near the real edges of the image [1]-[3]. map using OD filter is used to detect overshoot region, and then In this paper, the OR filtering method reduces ringing apply the OR filter which has been designed to reduce artifact caused by image resizing operations. Comparison overshoot. Finally combine the overshoot and ripple reduced between Gaussian filter is also done. The proposed method is images to obtain the ringing artifact reduced image. In second computationally faster and it produces visually finer images method, the weighted averaging of all the pixels within a without blurring the details and edges of the images. Ringing window of 3 × 3 is used to replace each pixel of the image. The artifact reduction technique is first applied to the downsized weights are determined by Gaussian function. The result image with truncation operation and then it is applied to the obtained in these two methods is compared in this paper. upsized image by zero padding. The proposed method Index Terms — DCT (discrete cosine transform), OD reduces the artifact and preserves the details and edges of the (Overshoot Detector), OR (overshoot-ripple) filter image. In Section II, the ringing artifact of the resized images is analyzed when resizing operations are performed in the DCT I. INTRODUCTION domain. In Section III, the ringing artifact reduction method using OR filter is given. In Section IV, filtering of ringing Ringing artifact appears as bands, ghosts near edges or artifact using OR filter has been explained and the echos when sharp transition takes place. Mathematically, this comparison between Gaussian filter are given in Section VI. artifact is called the Gibbs phenomenon. Ringing artifact can Experimental results are discussed in VII. Concluding be reduced by using various methods. These methods cannot remarks are given in Section VIII. remove serious artifact. Many computations have to be performed in order to estimate the ringing artifact and it II. RESIZING OPERATION causes serious blurring at edges and details of the image. Image resizing is the operation used to change the size of In frequency domain description, there is a possibility for the image. Truncation and zero padding can be used in DCT the generation of ringing artifact when the signal is domain for downsizing and upsizing of the image bandlimited or passed through a low-pass filter. In the time respectively. In truncation operation, the high frequency domain, ripples on sinc function produce ringing. Ringing coefficients of the image are discarded and in upsizing, occurs when a non-oscillating input yields an oscillating zeroes are added to the high frequency side. output. Ringing is closely related to overshoot which is when The resizing of the image in DCT domain [8] is explained the output takes on values higher than the maximum input below. The DCT operation has been used for resizing the value. image where block size of the DCT is chosen as 8X8. The Image resizing is done due to the advances of digital ringing artifact generated by the resizing operation is image processing. It is needed for various applications like analyzed here. image transmissions through the networks having varying In order to perform downsize operation on 8X8 DCT bandwidth. There are number of approaches have been block, take 8 sample sequences and apply type-II DCT. Then truncate high frequency coefficients of the image. Then apply 4-point IDCT. The same operations will be done for the Manuscript received March, 2013. upsizing operation also. Jinu Mathew , Electronics and Communication Karunya university, Coimbatore, Thamilnadu Shanty Chacko , Assistant Professor, Electronics and Communication, Karunya University, Coimbatore, Thamilnadu . Neethu Kuriakose , Electronics and Communication Karunya university, Coimbatore, Thamilnadu . 385 All Rights Reserved © 2013 IJARECE ISSN: 2278 – 909X International Journal of Advanced Research in Electronics and Communication Engineering (IJARECE) Volume 2, Issue 3, March 2013 III. RINGING ARTIFACT REDUCTION METHOD USING OR new low-pass filter, called as overshoot-ripple (OR) filter is FILTER used to reduce the ringing artifact. Figure 1 shows the block diagram of the ringing artifact The main-lobe width of the OR filter is to preserve the reduction method using OR filter. Image resizing includes details and edges on the resized images. The main-lobe width both downsizing and upsizing of the image in block-DCT is the distance from the location where the main-lobe domain is the first step, so that due to the transitions of this amplitude is equivalent to the maximum side-lobe amplitude image size ringing artifact will be produced near the edges of in the impulse response. The ratio of the main-lobe amplitude the image. The ringing artifact will be reduced only in the to the maximum side-lobe amplitude is called as ripple ratio. image blocks having the artifact above a threshold value. If it The main-lobe width can be calculated [9] as below, is below the threshold value, then the IDCT of image is taken ω = 2cos −1 (x / x ) (1) directly without filtering. R a β The blocks having ringing artifacts are filtered by the OR where, the parameter xa is found using this eqn filters with α1and α2.The image with artifact will be given as Dn (yk ) − a input to a filter, called as OR filter. The ripples will be (2) yk +1 = yk − β −1 reduced using the OR filter with α1. In order to detect the 2βCn−1 (yk ) overshoot region, an OD filter is designed and is used to which uses the inputs µ =β , n = N − 1, and ε = 10 -6 generate a mask. After finding the overshoot regions, OR filter with the designed value of α2 is applied in that region . D µ (x) is calculated using the following algorithm : The overshoot and ripples of the image is identified and n remove separately. • Step 1 Input µ, n, and ε. Image resizing in block µ , x π/ n DCT domain If = 0 then output = cos( 2 ) and stop. Set k = 1 , and compute n 2 + 2nµ − 2µ −1 No y = 1 n + µ ERinging ˃ E th • Step 2 Yes Compute D µ (y ) y = y − n k k+1 k 2µD µ+1 OR filter, OR filter, n−1 OD filter α1 α2 • Step 3 If |yk+1 – yk| ≤ ε, then output x= yk+1 and stop. Set k = k + 1 , and repeat from Step 2. IDCT IDCT IDCT IDCT Similarily, Ripple ratio can be calculated using the equation Mask-map generation D (y ) − a n k r yk+1 = yk − β −1 2βCn−1 (yk ) Overshoot region correction (3) ε -6 where the inputs µ= β, n=N-1, and = 10 Ringing artifact reduced image V. DESIGN OF OVERSHOOT -DETECTOR (OD) FILTER Figure 1. Block diagram of the ringing-artifact reduction method Overshoot detector filter can be designed using the using OR -filter following figure 2. The candidate OD filters can be obtained as follows The OR filter design includes the steps to find out the main-lobe width which will reduce the overshoot caused by F(n) > F N ' < n < N ' the increased value of α. The ripple ratio is also decided by th 1 2 for 0 ≤ n ≤ LN-1 (4 ) the value of α which should be chosen so as to reduce the F(n) <F otherwise th ripples. By taking the IDCT of the filtered image, the artifact ’ ’ removed image can be obtained. where N 1 and N 2 denotes the first and last sample indices of the negative overshoot of y OR( α2) (n) respectively. The IV. DESIGN OF OVERSHOOT -RIPPLE (OR) FILTER candidate OD filters which satisfy (4). In this paper, the ringing artifact reduction using OR filter H (k) = is explained. Ringing artifact is analyzed when zero-padding OR|DFT 2RN and truncation operations are performed in DCT domain. A 386 All Rights Reserved © 2013 IJARECE ISSN: 2278 – 909X International Journal of Advanced Research in Electronics and Communication Engineering (IJARECE) Volume 2, Issue 3, March 2013 will be the result when the low-pass filter is a Gaussian. In U α (k ) N 0 ≤ k ≤ N − 1 order to estimate the parameters from signals running 0 N ≤ k ≤ 2RN − N )5( averages to estimate parameters from signals with U α 2( RN − k ) 2RN − N + 1 ≤ k ≤ 2RN − 1 characteristics that vary with space and time. Gaussian filtering in one, two or three dimensions is among Mask map is generated by using an overshoot detector (OD) filter. Generated mask map which is a binary image the most commonly needed tasks in signal and image with 1 for the overshoot regions and 0 for the normal regions. processing. Finite impulse response filters in the time domain In the image domain, the ringing-artifact reduced image is with Gaussian masks are easy to implement in either floating composed as follows: or fixed point arithmetic, because Gaussian kernels are strictly positive and bounded.
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