Low-Complexity Lossless Coding of Asynchronous Event Sequences for Low-Power Chip Integration
The event sensor provides high temporal resolution and generates large amounts of raw event data. Efficient low-complexity coding solutions are required for integration into low-power event-processing chips with limited memory. In this paper, a novel lossless compression method is proposed for encod...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/24/10014 |
| _version_ | 1797455343300640768 |
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| author | Ionut Schiopu Radu Ciprian Bilcu |
| author_facet | Ionut Schiopu Radu Ciprian Bilcu |
| author_sort | Ionut Schiopu |
| collection | DOAJ |
| description | The event sensor provides high temporal resolution and generates large amounts of raw event data. Efficient low-complexity coding solutions are required for integration into low-power event-processing chips with limited memory. In this paper, a novel lossless compression method is proposed for encoding the event data represented as asynchronous event sequences. The proposed method employs only low-complexity coding techniques so that it is suitable for hardware implementation into low-power event-processing chips. A first, novel, contribution consists of a low-complexity coding scheme which uses a decision tree to reduce the representation range of the residual error. The decision tree is formed by using a triplet threshold parameter which divides the input data range into several coding ranges arranged at concentric distances from an initial prediction, so that the residual error of the true value information is represented by using a reduced number of bits. Another novel contribution consists of an improved representation, which divides the input sequence into same-timestamp subsequences, wherein each subsequence collects the same timestamp events in ascending order of the largest dimension of the event spatial information. The proposed same-timestamp representation replaces the event timestamp information with the same-timestamp subsequence length and encodes it together with the event spatial and polarity information into a different bitstream. Another novel contribution is the random access to any time window by using additional header information. The experimental evaluation on a highly variable event density dataset demonstrates that the proposed low-complexity lossless coding method provides an average improvement of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>5.49</mn><mo>%</mo></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>11.45</mn><mo>%</mo></mrow></semantics></math></inline-formula>, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>35.57</mn><mo>%</mo></mrow></semantics></math></inline-formula> compared with the state-of-the-art performance-oriented lossless data compression codecs Bzip2, LZMA, and ZLIB, respectively. To our knowledge, the paper proposes the first low-complexity lossless compression method for encoding asynchronous event sequences that are suitable for hardware implementation into low-power chips. |
| first_indexed | 2024-03-09T15:52:03Z |
| format | Article |
| id | doaj.art-e9c67f38a33a454386066e4487858a92 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T15:52:03Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-e9c67f38a33a454386066e4487858a922023-11-24T17:59:06ZengMDPI AGSensors1424-82202022-12-0122241001410.3390/s222410014Low-Complexity Lossless Coding of Asynchronous Event Sequences for Low-Power Chip IntegrationIonut Schiopu0Radu Ciprian Bilcu1Tampere Handset Camera Innovation Lab, Huawei Technologies Oy (Finland) Co., Ltd., 33720 Tampere, FinlandTampere Handset Camera Innovation Lab, Huawei Technologies Oy (Finland) Co., Ltd., 33720 Tampere, FinlandThe event sensor provides high temporal resolution and generates large amounts of raw event data. Efficient low-complexity coding solutions are required for integration into low-power event-processing chips with limited memory. In this paper, a novel lossless compression method is proposed for encoding the event data represented as asynchronous event sequences. The proposed method employs only low-complexity coding techniques so that it is suitable for hardware implementation into low-power event-processing chips. A first, novel, contribution consists of a low-complexity coding scheme which uses a decision tree to reduce the representation range of the residual error. The decision tree is formed by using a triplet threshold parameter which divides the input data range into several coding ranges arranged at concentric distances from an initial prediction, so that the residual error of the true value information is represented by using a reduced number of bits. Another novel contribution consists of an improved representation, which divides the input sequence into same-timestamp subsequences, wherein each subsequence collects the same timestamp events in ascending order of the largest dimension of the event spatial information. The proposed same-timestamp representation replaces the event timestamp information with the same-timestamp subsequence length and encodes it together with the event spatial and polarity information into a different bitstream. Another novel contribution is the random access to any time window by using additional header information. The experimental evaluation on a highly variable event density dataset demonstrates that the proposed low-complexity lossless coding method provides an average improvement of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>5.49</mn><mo>%</mo></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>11.45</mn><mo>%</mo></mrow></semantics></math></inline-formula>, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>35.57</mn><mo>%</mo></mrow></semantics></math></inline-formula> compared with the state-of-the-art performance-oriented lossless data compression codecs Bzip2, LZMA, and ZLIB, respectively. To our knowledge, the paper proposes the first low-complexity lossless compression method for encoding asynchronous event sequences that are suitable for hardware implementation into low-power chips.https://www.mdpi.com/1424-8220/22/24/10014low-power electronicslow-complexity codeclossless compressioevent camera |
| spellingShingle | Ionut Schiopu Radu Ciprian Bilcu Low-Complexity Lossless Coding of Asynchronous Event Sequences for Low-Power Chip Integration Sensors low-power electronics low-complexity codec lossless compressio event camera |
| title | Low-Complexity Lossless Coding of Asynchronous Event Sequences for Low-Power Chip Integration |
| title_full | Low-Complexity Lossless Coding of Asynchronous Event Sequences for Low-Power Chip Integration |
| title_fullStr | Low-Complexity Lossless Coding of Asynchronous Event Sequences for Low-Power Chip Integration |
| title_full_unstemmed | Low-Complexity Lossless Coding of Asynchronous Event Sequences for Low-Power Chip Integration |
| title_short | Low-Complexity Lossless Coding of Asynchronous Event Sequences for Low-Power Chip Integration |
| title_sort | low complexity lossless coding of asynchronous event sequences for low power chip integration |
| topic | low-power electronics low-complexity codec lossless compressio event camera |
| url | https://www.mdpi.com/1424-8220/22/24/10014 |
| work_keys_str_mv | AT ionutschiopu lowcomplexitylosslesscodingofasynchronouseventsequencesforlowpowerchipintegration AT raduciprianbilcu lowcomplexitylosslesscodingofasynchronouseventsequencesforlowpowerchipintegration |