Memory efficient and constant time 2D-recursive spatial averaging filter for embedded implementations

AbstractThe most commonly used strategy for peptide identification in shotgun LC-MS/MS proteomics involves searching of MS/MS data against an in-silico digested protein sequence database. Typically, the digested peptide sequences are indexed into the memory to allow faster search times. However, subjecting a database to post-translational modifications (PTMs) during digestion results in an exponential increase in the number of peptides and therefore memory consumption. This limits the usage of existing fragment-ion based open-search algorithms for databases with several PTMs. In this paper, we propose a novel fragment-ion indexing technique which is analogous to suffix array transformation and allows constant time querying of indexed ions. We extend our transformation method, called SLM-Transform, by constructing ion buckets that allow querying of all indexed ions by mass by only storing information on distribution of ion-frequencies within buckets. The stored information is used with a regression technique to locate the position of ions in constant time. Moreover, the number of theoretical b- and y-ions generated and indexed for each theoretical spectrum are limited. Our results show that SLM-Transform allows indexing of up to 4x peptides than other leading fragment-ion based database search tools within the same memory constraints. We show that SLM-Transform based index allows indexing of over 83 million peptides within 26GB RAM as compared to 80GB required by MSFragger. Finally, we show the constant ion retrieval time for SLM-Transform based index allowing ultrafast peptide search speeds.Source code will be made available at: https://github.com/pcdslab/slmindex

Download Full-text

Conductivity image enhancement in MREIT using adaptively weighted spatial averaging filter

BioMedical Engineering OnLine ◽

10.1186/1475-925x-13-87 ◽

2014 ◽

Vol 13 (1) ◽

pp. 87

Author(s):

Tong Oh ◽

Hyung Kim ◽

Woo Jeong ◽

Hun Wi ◽

Oh Kwon ◽

...

Keyword(s):

Image Enhancement ◽

Spatial Averaging ◽

Averaging Filter ◽

Conductivity Image

Download Full-text

Hash-Based Hierarchical Caching and Layered Filtering for Interactive Previews in Global Illumination Rendering

Computers ◽

10.3390/computers9010017 ◽

2020 ◽

Vol 9 (1) ◽

pp. 17

Author(s):

Thorsten Roth ◽

Martin Weier ◽

Pablo Bauszat ◽

André Hinkenjann ◽

Yongmin Li

Keyword(s):

Monte Carlo ◽

Computational Complexity ◽

Global Illumination ◽

Ground Truth ◽

Low Noise ◽

Constant Time ◽

Efficient Storage ◽

Diffuse Illumination ◽

Interactive Frame ◽

Memory Efficient

Modern Monte-Carlo-based rendering systems still suffer from the computational complexity involved in the generation of noise-free images, making it challenging to synthesize interactive previews. We present a framework suited for rendering such previews of static scenes using a caching technique that builds upon a linkless octree. Our approach allows for memory-efficient storage and constant-time lookup to cache diffuse illumination at multiple hitpoints along the traced paths. Non-diffuse surfaces are dealt with in a hybrid way in order to reconstruct view-dependent illumination while maintaining interactive frame rates. By evaluating the visual fidelity against ground truth sequences and by benchmarking, we show that our approach compares well to low-noise path-traced results, but with a greatly reduced computational complexity, allowing for interactive frame rates. This way, our caching technique provides a useful tool for global illumination previews and multi-view rendering.

Download Full-text

Adaptive fast spatial averaging filter

2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT) ◽

10.1109/icccnt.2017.8203929 ◽

2017 ◽

Author(s):

Rajesh Reddy Datla

Keyword(s):

Spatial Averaging ◽

Averaging Filter

Download Full-text

Hash-Based Hierarchical Caching and Layered Filtering for Interactive Previews in Global Illumination Rendering

10.20944/preprints202001.0247.v1 ◽

2020 ◽

Author(s):

Thorsten Roth ◽

Martin Weier ◽

Pablo Bauszat ◽

André Hinkenjann ◽

Yongmin Li

Keyword(s):

Monte Carlo ◽

Computational Complexity ◽

Global Illumination ◽

Ground Truth ◽

Low Noise ◽

Constant Time ◽

Efficient Storage ◽

Diffuse Illumination ◽

Interactive Frame ◽

Memory Efficient

Modern Monte-Carlo-based rendering systems still suffer from the computational complexity involved in the generation of noise-free images, making it challenging to synthesize interactive previews. We present a framework suited for rendering such previews of static scenes using a caching technique that builds upon a linkless octree. Our approach allows for memory-efficient storage and constant-time lookup to cache diffuse illumination at multiple hitpoints along the traced paths. Non-diffuse surfaces are dealt with in a hybrid way in order to reconstruct view-dependent illumination while maintaining interactive frame rates. By evaluating the visual fidelity against ground truth sequences and by benchmarking, we show that our approach compares well to low-noise path traced results, but with a greatly reduced computational complexity allowing for interactive frame rates. This way, our caching technique provides a useful tool for global illumination previews and multi-view rendering.

Download Full-text