Baru-baru ini, penggunaan alat-alat digital semakin meningkat di kalangan masyarakat, tetapi penggunaan alat-alat ini juga terdapat batasannya. Salah satu batasan adalah kemunculan hingar dalam gambar yang diambil dengan pendedahan masa yang panjang. Pendedahan masa yang panjang untuk mengambil gambar adalah diperlukan apabila gambar diambil dalam keadaan yang gelap seperti gambar yang diambil pada waktu malam atau yang diambil dalam bilik auditorium. Gambar forensik juga adalah gambar yang memerlukan pendedahan masa yang panjang. Hingar yang selalu wujud dalam keadaan ini dinamakan sebagai hingar “salt and pepper”. Hingar ini dinamakan “salt and pepper” kerana ia menunjukkan ketidaklicinan yang wujud dalam suatu gambar. Tujuan projek ini adalah untuk mengembangkan satu teknik untuk mengurangkan hingar jenis ini yang wujud dalam gambar. Dalam pelbagai jenis filter yang telah dikemukakan, teknik yang digunakan dalam projek ini adalah penuras median dengan menggunakan perisian Borland C++ 5.5 bagi menglengkapkan projek ini. Penuras tak lelurus ini dapat mengurangkan hingar dalam suatu gambar yang disebabkan oleh eksperiment ataupun lalat dalam sesuatu titik. Nilai ralat purata punca kuasadua dikirakan bagi membandingkan keputusan yang diambil. Terdapat sebanyak 13 jenis penuras median digunakan dalam projek ini seperti “square with causal and iterative median filtering”, “circle with causal and iterative median filtering”, “stick with causal and iterative median filtering”, “square with causal and non-iterative median filtering”, “circle with causal and non-iterative median filtering”, “stick with causal and non-iterative median filtering”, “square with non-causal and iterative median filtering”, “circle with non-causal and iterative median filtering”, “stick with non-causal and iterative median filtering”, “square with non-causal and non- iterative median filtering”, “circle with non-causal and non-iterative median filtering”, “stick with non-causal and non-iterative median filtering” and “progressive switching median filtering”. Pada akhir projek, saya bercadangkan penggunaan penuras jenis “progressive switching median” adalah terbaik bagi mengurangkan hingar”salt and pepper” dalam suatu gambar. Eksperiment telah dilakukan dan ia telah menunjukkan keputusan yang berkesan dengan mengurangkan hingar dalam gambar tanpa menjejaskan kualiti gambar.
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Nowadays, the popularity of digital devices increases. However there are still some limitations in digital technology. One of the limitations is the appearance of additive noise in the images that are acquired using long exposure times. Long exposure times are needed in the case when we need to take an image under the conditions that have a low level of illumination, such as during the night time or in a large room such as in an auditorium. Forensics images are also included as the images which need a long exposure time. Noise that is often appears in such conditions is “salt-and-pepper” noise. This noise is called “salt and pepper” because the granular appearance of individual points of noise in the signal. The objective of this project is to find the best way to reduce this type of noise in digital images. From various branched of filter in image processing field, I had chosen median filter as the technique to reduce noise by using Borland C++ compiler 5.5 to complete the project. This nonlinear technique can remove single-point noise caused by experimental errors, or other sampling errors that occur at single points due to bad pixels or other causes. A mean square error measurement was used for comparison of the results. There are 13 different median filtering technique used in the project which are square with causal and iterative median filtering, circle with causal and iterative median filtering, stick with causal and iterative median filtering, square with causal and non-iterative median filtering, circle with causal and non-iterative median filtering, stick with causal and non-iterative median filtering, square with non-causal and iterative median filtering, circle with non-causal and iterative median filtering, stick with non-causal and iterative median filtering, square with non- causal and non-iterative median filtering, circle with non-causal and non-iterative median filtering, stick with non-causal and non-iterative median filtering and progressive switching median filtering. At the end of the project, I suggest the best filter which can used to reduce “salt and pepper” noise in the image is progressive switching median filtering technique. Experiments have shown this technique extensively reduces the noise in an image with no obvious loss of image sharpness.
Noise reduction for digital images using median filtering technique_Teoh Sin Hoong_E3_2006_NI