Dalam dunia fotografi digital, memang tidak dapat dinafikan bahawa hampir
semua orang memiliki kamera digital. Mereka boleh memiliki kamera digital kompak,
kamera digital SLR ataupun telefon bimbit yang berkamera. Oleh itu. gambar yang
telah diambil oleh kamera mungkin mempunyai hingar atau kabur. Banyak cara untuk
menilai kualiti gambar telah pun dihasilkan dan digunakan. Namun begitu, setiap cara
mempunyai kebaikan dan keburukannya. Justeru, penilaian haruslah dilaksanakan untuk
membandingkan cara-cara tersebut. Pertama sekali, pelbagai gambar dengan tahap
hingar, kontras, kabur dan herotan yang berbeza telah dihasilkan. Kemudian, setiap
teknik penilaian kualiti gambar telah dilaksanakan. Sebanyak lima belas teknik
penilaian telah dilaksanakan dalam projek ini. Seterusnya semua gambar yang
dihasilkan akan dinilai dengan teknik penilaian yang telah dihasilkan. Satu tinjauan
untuk menilai kualiti gambar juga dilaksanakan. Setiap data penilaian dan tinjauan akan
dikumpulkan serta dibandingkan. Akhir sekali, teknik yang memberikan prestasi terbaik
dapat ditentukan. Daripada keputusan yang direkodkan, kesesuaian teknik penilaian
untuk degradasi gambar berbeza dapat ditentukan. Dengan perbandingan antara teknik
penilaian matematik dan tinjauan, adalah didapati bahawa tinjauan menunjukkan
persaingan kepada penilaian matematik.
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In this digital world of photography, it cannot be denied that almost everyone
has a digital camera. It can either be a compact digital camera, digital SLR camera or
even a mobile phone with camera. Therefore, it is very common occasion that images
that are taken from a camera to be blurry or noisy. Many methods in image quality
measures have already been developed and from all these methods, there are pros and
cons of each measure. Hence an evaluation has to be done to compare these methods.
Firstly, multiple images with different noise level, contrast level, blurring level and
distortion is generated. Secondly, each methods of quality measure are implemented.
There are as much as fifteen methods of evaluation that are implemented in this project.
The next step is to do measurement on the images using the methods that are
implemented. A human survey to determine image quality is done as well. Results of
each measurement and human survey are collected and comparison is made. Finally,
method with the best performance is determined. From the results obtained, certain
methods can be proved to be suitable for certain degradation of images. With the
comparison of the mathematical evaluations with the human survey, it is shown that the
survey has an accurate result as well as the mathematical methods. As conclusion,
universal quality index and structural similarity index show the best sensitivity in image
quality measure.
Evaluations of quality measures for grayscale digital image / Lee Chee Keng