Specifications  The method of wavelet thresholding for removing noise, or denoising, has been researched extensively \ due to its effectiveness and simplicity Amjed AlFahoum 
Business section 

Specifications  The method of wavelet thresholding for removing noise, or denoising, has been researched extensively \ due to its effectiveness and simplicity Amjed AlFahoum 
Business section 

Specifications  The method of wavelet thresholding for removing noise, or denoising, has been researched extensively \ due to its effectiveness and simplicity Amjed AlFahoum 
Outline  1. Introduction 2. 1D Resampling 3. 2D Image Resizing 4. 2D Image Rotation FPGA Implementation Conclusion References 
Suggested Link Details/Purchase 

Content  shown in Figure 1. The primary advantage of this structure is the filters run at ¼ the input sample rate. H1(z1) H2(z1) H0(z1) H3(z1) y(m)x(n) Figure 1 Polyphase Decimator Upsampling requires interpolation of digital data and requires one to pay attention to “images” of the original spectra. For example, if we were interpolating by 3 a 256 pixel line to 768 pixels one would utilize a filter to reject the “image” spectra. This structure is usually implemented as a polyphase interpolator shown in Figure 2. Note that the three filters in this structure run at the low input sample rate in contrast to the high sample rate of the output stream. H1(z1) H2(z1) H0(z1) y(m)x(n) Figure 2 Polyphase Interpolator To perform upsampling at various interpolation rates a fractional filter needs to be designed. Consider the case of 512 input samples with desired up sample by 4 (2048) and resolution of 16 pixels. A polyphase fractional upsampling architecture is presented in Figure 3 that allows P/Q resampling [5]. In this structure P polyphase filters are used with a Q sequencer to determine filter utilization. In the present example Q is 512/16 or 32. The number of filter banks (P) is defined by 2048/16 (128). During the actual operation of the P/Q resampling the number of P filters included in the sequencing of Q is determined by the upsampling rate. The design of the actual filters is application dependent. For image processing linear and cubic have been widely accepted in order to keep the filter lengths to a minimum. Implementation of this polyphase upsampling filter is usually carried out with a single filter with a coefficient bank. h0(n) h1(n) hp3(n) fs d(n) 1:Q d()Pn+r Q fsP Q hp2(n) hp1(n) Figure 3 Polyphase Resampling To design a system which can both down sample by 4 and upsample by 2 with resultion of 16 pixels we can utilize the polyphase resampling structure. In this case the sequencer would require a skip condition where a sample has been input but no sample is extracted from the polyphase structure. It can be shown that the overall filter response during decimation is providing the necessary aliasing protection. For this resampling case Q is 32, P is 64, and the range of filters included in the computation is 8 to 64 to support 128 to 1024 pixel sizes. 3. 2D Image Resizing Extending the resampling to two dimensions for the purpose of imaging or video applications involves considerations for the filter design and the impact on the Human Visual System (HVS). Preservation of edges and noise characteristics play a major role in this area of research. In this paper we will not address this issue but rather explore current algorithm and architecture tradeoffs. We have considered the design parameters (range and resolution) as they relate to the one dimensional polyphase resampling. Extending our current example to two dimensions consider a 512x512 image which we would like 
Navigation  Previous Page / Next Page 
Following Datasheets  rotbf (3 pages) Rothenberger (29 pages) rotsf (3 pages) round_datasheet (3 pages) Route_AccountingMobile_Printing (2 pages) RoweBots_Unison4_DS (3 pages) RoweBots_Unison5_DS (3 pages) Rox_Anderson_3_22_07 (2 pages) rp (93 pages) rp1a090zp (6 pages) 
Check in eportals  WorldHNews Products Extensions Partners Automation Jet Parts 
Sitemap Folder  group1 group2 group3 group4 group5 group6 group7 group8 group9 group10 group11 group12 group13 group14 group15 group16 group17 group18 group19 group20 group21 group22 group23 group24 group25 group26 group27 group28 group29 group30 group31 group32 group33 group34 group35 group36 group37 group38 group39 group40 group41 group42 group43 group44 group45 group46 group47 group48 group49 group50 group51 group52 group53 group54 group55 group56 group57 group58 group59 group60 group61 group62 group63 group64 group65 group66 group67 group68 group69 group70 group71 group72 group73 group74 group75 group76 group77 group78 group79 group80 group81 group82 group83 group84 group85 group86 group87 group88 group89 group90 group91 group92 group93 group94 group95 group96 group97 group98 group99 group100 Prewious Folder Next Folder 