Design of a 2D Median Filter with a High Throughput FPGA Implementation
Bibliographic record
Abstract
In this paper, a hybrid technique for median filtering of images affected by impulse noise is proposed. Our technique combines impulse noise detection, histogram-based median calculation and bit-plane processing to obtain approximate median with the aim of optimizing the throughput at minimum cost of image quality. The proposed median filter is implemented on FPGA with pipelining and is significantly faster than existing FPGA based pipelined median filter architectures. Implementation of the proposed median filter hardware provides a throughput of 282 Full High Definition (FHD) frames per second on Zynq-7 FPGA; 48% higher than the throughput of low-latency median filter. Compared to FPGA implementation of a low complexity noise removal, the proposed median filter utilizes only 45% of FPGA slices and provides a speed-up of 2.2 on Zynq-7 FPGA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".